dont cache deps

- Fix OSError when trying to get source code of lambda functions in guardrail events
- Gracefully handle lambdas and built-in functions by showing placeholder text

.github/workflows/build-uv-cache.yml

@@ -33,7 +33,7 @@ jobs:
       - name: Install dependencies and populate cache
         run: |
           echo "Building global UV cache for Python ${{ matrix.python-version }}..."
-          uv sync --all-groups --all-extras --no-install-project
+          uv sync --all-groups --all-extras
           echo "Cache populated successfully"
 
       - name: Save uv caches

.github/workflows/codeql.yml

@@ -15,11 +15,11 @@ on:
   push:
     branches: [ "main" ]
     paths-ignore:
-      - "lib/crewai/src/crewai/cli/templates/**"
+      - "src/crewai/cli/templates/**"
   pull_request:
     branches: [ "main" ]
     paths-ignore:
-      - "lib/crewai/src/crewai/cli/templates/**"
+      - "src/crewai/cli/templates/**"
 
 jobs:
   analyze:

.github/workflows/linter.yml

@@ -38,7 +38,7 @@ jobs:
           enable-cache: false
 
       - name: Install dependencies
-        run: uv sync --all-groups --all-extras --no-install-project
+        run: uv sync --all-packages --all-extras --no-install-project
 
       - name: Get Changed Python Files
         id: changed-files
@@ -52,10 +52,10 @@ jobs:
       - name: Run Ruff on Changed Files
         if: ${{ steps.changed-files.outputs.files != '' }}
         run: |
-         echo "${{ steps.changed-files.outputs.files }}" \
-           | tr ' ' '\n' \
-           | grep -v 'src/crewai/cli/templates/' \
-           | xargs -I{} uv run ruff check "{}"
+          echo "${{ steps.changed-files.outputs.files }}" \
+            | tr ' ' '\n' \
+            | grep -v 'src/crewai/cli/templates/' \
+            | xargs -I{} uv run ruff check "{}"
 
       - name: Save uv caches
         if: steps.cache-restore.outputs.cache-hit != 'true'

.github/workflows/publish.yml

@@ -1,71 +0,0 @@
-name: Publish to PyPI
-
-on:
-  release:
-    types: [ published ]
-  workflow_dispatch:
-
-jobs:
-  build:
-    if: github.event.release.prerelease == true
-    name: Build packages
-    runs-on: ubuntu-latest
-    permissions:
-        contents: read
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: "3.12"
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@v4
-
-      - name: Build packages
-        run: |
-          uv build --all-packages
-          rm dist/.gitignore
-
-      - name: Upload artifacts
-        uses: actions/upload-artifact@v4
-        with:
-          name: dist
-          path: dist/
-
-  publish:
-    if: github.event.release.prerelease == true
-    name: Publish to PyPI
-    needs: build
-    runs-on: ubuntu-latest
-    environment:
-      name: pypi
-      url: https://pypi.org/p/crewai
-    permissions:
-      id-token: write
-      contents: read
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@v6
-        with:
-          version: "0.8.4"
-          python-version: "3.12"
-          enable-cache: false
-
-      - name: Download artifacts
-        uses: actions/download-artifact@v4
-        with:
-          name: dist
-          path: dist
-
-      - name: Publish to PyPI
-        env:
-          UV_PUBLISH_TOKEN: ${{ secrets.PYPI_API_TOKEN }}
-        run: |
-          for package in dist/*; do
-            echo "Publishing $package"
-            uv publish "$package"
-          done

.github/workflows/tests.yml

@@ -8,14 +8,6 @@ permissions:
 env:
   OPENAI_API_KEY: fake-api-key
   PYTHONUNBUFFERED: 1
-  BRAVE_API_KEY: fake-brave-key
-  SNOWFLAKE_USER: fake-snowflake-user
-  SNOWFLAKE_PASSWORD: fake-snowflake-password
-  SNOWFLAKE_ACCOUNT: fake-snowflake-account
-  SNOWFLAKE_WAREHOUSE: fake-snowflake-warehouse
-  SNOWFLAKE_DATABASE: fake-snowflake-database
-  SNOWFLAKE_SCHEMA: fake-snowflake-schema
-  EMBEDCHAIN_DB_URI: sqlite:///test.db
 
 jobs:
   tests:
@@ -33,17 +25,17 @@ jobs:
         with:
           fetch-depth: 0  # Fetch all history for proper diff
 
-      - name: Restore global uv cache
-        id: cache-restore
-        uses: actions/cache/restore@v4
-        with:
-          path: |
-            ~/.cache/uv
-            ~/.local/share/uv
-            .venv
-          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
-          restore-keys: |
-            uv-main-py${{ matrix.python-version }}-
+      # - name: Restore global uv cache
+      #   id: cache-restore
+      #   uses: actions/cache/restore@v4
+      #   with:
+      #     path: |
+      #       ~/.cache/uv
+      #       ~/.local/share/uv
+      #       .venv
+      #     key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
+      #     restore-keys: |
+      #       uv-main-py${{ matrix.python-version }}-
 
       - name: Install uv
         uses: astral-sh/setup-uv@v6
@@ -53,18 +45,18 @@ jobs:
           enable-cache: false
 
       - name: Install the project
-        run: uv sync --all-groups --all-extras
+        run: uv sync --all-packages --all-extras
 
-      - name: Restore test durations
-        uses: actions/cache/restore@v4
-        with:
-          path: .test_durations_py*
-          key: test-durations-py${{ matrix.python-version }}
+      # - name: Restore test durations
+      #   uses: actions/cache/restore@v4
+      #   with:
+      #     path: .test_durations_py*
+      #     key: test-durations-py${{ matrix.python-version }}
 
       - name: Run tests (group ${{ matrix.group }} of 8)
         run: |
           PYTHON_VERSION_SAFE=$(echo "${{ matrix.python-version }}" | tr '.' '_')
-          DURATION_FILE="../../.test_durations_py${PYTHON_VERSION_SAFE}"
+          DURATION_FILE=".test_durations_py${PYTHON_VERSION_SAFE}"
 
           # Temporarily always skip cached durations to fix test splitting
           # When durations don't match, pytest-split runs duplicate tests instead of splitting
@@ -83,7 +75,7 @@ jobs:
           #   DURATIONS_ARG="--durations-path=${DURATION_FILE}"
           # fi
 
-          cd lib/crewai && uv run pytest \
+          uv run pytest lib/crewai \
             --block-network \
             --timeout=30 \
             -vv \
@@ -92,27 +84,15 @@ jobs:
             $DURATIONS_ARG \
             --durations=10 \
             -n auto \
-            --maxfail=3
+            --maxfail=3 \
+            -m "not requires_local_services"
 
-      - name: Run tool tests (group ${{ matrix.group }} of 8)
-        run: |
-          cd lib/crewai-tools && uv run pytest \
-            --block-network \
-            --timeout=30 \
-            -vv \
-            --splits 8 \
-            --group ${{ matrix.group }} \
-            --durations=10 \
-            -n auto \
-            --maxfail=3
-
-
-      - name: Save uv caches
-        if: steps.cache-restore.outputs.cache-hit != 'true'
-        uses: actions/cache/save@v4
-        with:
-          path: |
-            ~/.cache/uv
-            ~/.local/share/uv
-            .venv
-          key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
+      # - name: Save uv caches
+      #   if: steps.cache-restore.outputs.cache-hit != 'true'
+      #   uses: actions/cache/save@v4
+      #   with:
+      #     path: |
+      #       ~/.cache/uv
+      #       ~/.local/share/uv
+      #       .venv
+      #     key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}

.github/workflows/type-checker.yml

@@ -40,7 +40,7 @@ jobs:
           enable-cache: false
 
       - name: Install dependencies
-        run: uv sync --all-groups --all-extras
+        run: uv sync --all-packages --all-extras
 
       - name: Get changed Python files
         id: changed-files

.pre-commit-config.yaml

@@ -6,16 +6,19 @@ repos:
         entry: uv run ruff check
         language: system
         types: [python]
+        files: ^lib/crewai/src/
         exclude: ^lib/crewai/
       - id: ruff-format
         name: ruff-format
         entry: uv run ruff format
         language: system
         types: [python]
+        files: ^lib/crewai/src/
         exclude: ^lib/crewai/
       - id: mypy
         name: mypy
         entry: uv run mypy
         language: system
         types: [python]
+        files: ^lib/crewai/src/
         exclude: ^lib/crewai/

README.md

@@ -62,9 +62,9 @@
 With over 100,000 developers certified through our community courses at [learn.crewai.com](https://learn.crewai.com), CrewAI is rapidly becoming the
 standard for enterprise-ready AI automation.
 
-# CrewAI AMP Suite
+# CrewAI Enterprise Suite
 
-CrewAI AMP Suite is a comprehensive bundle tailored for organizations that require secure, scalable, and easy-to-manage agent-driven automation.
+CrewAI Enterprise Suite is a comprehensive bundle tailored for organizations that require secure, scalable, and easy-to-manage agent-driven automation.
 
 You can try one part of the suite the [Crew Control Plane for free](https://app.crewai.com)
 
@@ -76,9 +76,9 @@ You can try one part of the suite the [Crew Control Plane for free](https://app.
 - **Advanced Security**: Built-in robust security and compliance measures ensuring safe deployment and management.
 - **Actionable Insights**: Real-time analytics and reporting to optimize performance and decision-making.
 - **24/7 Support**: Dedicated enterprise support to ensure uninterrupted operation and quick resolution of issues.
-- **On-premise and Cloud Deployment Options**: Deploy CrewAI AMP on-premise or in the cloud, depending on your security and compliance requirements.
+- **On-premise and Cloud Deployment Options**: Deploy CrewAI Enterprise on-premise or in the cloud, depending on your security and compliance requirements.
 
-CrewAI AMP is designed for enterprises seeking a powerful, reliable solution to transform complex business processes into efficient,
+CrewAI Enterprise is designed for enterprises seeking a powerful, reliable solution to transform complex business processes into efficient,
 intelligent automations.
 
 ## Table of contents
@@ -674,9 +674,9 @@ CrewAI is released under the [MIT License](https://github.com/crewAIInc/crewAI/b
 
 ### Enterprise Features
 
-- [What additional features does CrewAI AMP offer?](#q-what-additional-features-does-crewai-amp-offer)
-- [Is CrewAI AMP available for cloud and on-premise deployments?](#q-is-crewai-amp-available-for-cloud-and-on-premise-deployments)
-- [Can I try CrewAI AMP for free?](#q-can-i-try-crewai-amp-for-free)
+- [What additional features does CrewAI Enterprise offer?](#q-what-additional-features-does-crewai-enterprise-offer)
+- [Is CrewAI Enterprise available for cloud and on-premise deployments?](#q-is-crewai-enterprise-available-for-cloud-and-on-premise-deployments)
+- [Can I try CrewAI Enterprise for free?](#q-can-i-try-crewai-enterprise-for-free)
 
 ### Q: What exactly is CrewAI?
 
@@ -732,17 +732,17 @@ A: Check out practical examples in the [CrewAI-examples repository](https://gith
 
 A: Contributions are warmly welcomed! Fork the repository, create your branch, implement your changes, and submit a pull request. See the Contribution section of the README for detailed guidelines.
 
-### Q: What additional features does CrewAI AMP offer?
+### Q: What additional features does CrewAI Enterprise offer?
 
-A: CrewAI AMP provides advanced features such as a unified control plane, real-time observability, secure integrations, advanced security, actionable insights, and dedicated 24/7 enterprise support.
+A: CrewAI Enterprise provides advanced features such as a unified control plane, real-time observability, secure integrations, advanced security, actionable insights, and dedicated 24/7 enterprise support.
 
-### Q: Is CrewAI AMP available for cloud and on-premise deployments?
+### Q: Is CrewAI Enterprise available for cloud and on-premise deployments?
 
-A: Yes, CrewAI AMP supports both cloud-based and on-premise deployment options, allowing enterprises to meet their specific security and compliance requirements.
+A: Yes, CrewAI Enterprise supports both cloud-based and on-premise deployment options, allowing enterprises to meet their specific security and compliance requirements.
 
-### Q: Can I try CrewAI AMP for free?
+### Q: Can I try CrewAI Enterprise for free?
 
-A: Yes, you can explore part of the CrewAI AMP Suite by accessing the [Crew Control Plane](https://app.crewai.com) for free.
+A: Yes, you can explore part of the CrewAI Enterprise Suite by accessing the [Crew Control Plane](https://app.crewai.com) for free.
 
 ### Q: Does CrewAI support fine-tuning or training custom models?
 
@@ -762,7 +762,7 @@ A: CrewAI is highly scalable, supporting simple automations and large-scale ente
 
 ### Q: Does CrewAI offer debugging and monitoring tools?
 
-A: Yes, CrewAI AMP includes advanced debugging, tracing, and real-time observability features, simplifying the management and troubleshooting of your automations.
+A: Yes, CrewAI Enterprise includes advanced debugging, tracing, and real-time observability features, simplifying the management and troubleshooting of your automations.
 
 ### Q: What programming languages does CrewAI support?
 

docs/docs.json

@@ -9,22 +9,7 @@
   },
   "favicon": "/images/favicon.svg",
   "contextual": {
-    "options": [
-      "copy",
-      "view",
-      "chatgpt",
-      "claude",
-      "perplexity",
-      "mcp",
-      "cursor",
-      "vscode",
-      {
-        "title": "Request a feature",
-        "description": "Join the discussion on GitHub to request a new feature",
-        "icon": "plus",
-        "href": "https://github.com/crewAIInc/crewAI/issues/new/choose"
-      }
-    ]
+    "options": ["copy", "view", "chatgpt", "claude"]
   },
   "navigation": {
     "languages": [
@@ -55,16 +40,6 @@
           ]
         },
         "tabs": [
-          {
-            "tab": "Home",
-            "icon": "house",
-            "groups": [
-              {
-                "group": "Welcome",
-                "pages": ["index"]
-              }
-            ]
-          },
           {
             "tab": "Documentation",
             "icon": "book-open",
@@ -250,9 +225,9 @@
                     "group": "Integrations",
                     "icon": "plug",
                     "pages": [
-                      "en/tools/integration/overview",
-                      "en/tools/integration/bedrockinvokeagenttool",
-                      "en/tools/integration/crewaiautomationtool"
+                      "en/tools/tool-integrations/overview",
+                      "en/tools/tool-integrations/bedrockinvokeagenttool",
+                      "en/tools/tool-integrations/crewaiautomationtool"
                     ]
                   },
                   {
@@ -271,10 +246,8 @@
               {
                 "group": "Observability",
                 "pages": [
-                  "en/observability/tracing",
                   "en/observability/overview",
                   "en/observability/arize-phoenix",
-                  "en/observability/braintrust",
                   "en/observability/langdb",
                   "en/observability/langfuse",
                   "en/observability/langtrace",
@@ -304,7 +277,6 @@
                   "en/learn/force-tool-output-as-result",
                   "en/learn/hierarchical-process",
                   "en/learn/human-input-on-execution",
-                  "en/learn/human-in-the-loop",
                   "en/learn/kickoff-async",
                   "en/learn/kickoff-for-each",
                   "en/learn/llm-connections",
@@ -321,7 +293,7 @@
             ]
           },
           {
-            "tab": "AMP",
+            "tab": "Enterprise",
             "icon": "briefcase",
             "groups": [
               {
@@ -329,27 +301,15 @@
                 "pages": ["en/enterprise/introduction"]
               },
               {
-                "group": "Build",
+                "group": "Features",
                 "pages": [
-                  "en/enterprise/features/automations",
-                  "en/enterprise/features/crew-studio",
-                  "en/enterprise/features/marketplace",
-                  "en/enterprise/features/agent-repositories",
-                  "en/enterprise/features/tools-and-integrations"
-                ]
-              },
-              {
-                "group": "Operate",
-                "pages": [
-                  "en/enterprise/features/traces",
+                  "en/enterprise/features/rbac",
+                  "en/enterprise/features/tool-repository",
                   "en/enterprise/features/webhook-streaming",
-                  "en/enterprise/features/hallucination-guardrail"
-                ]
-              },
-              {
-                "group": "Manage",
-                "pages": [
-                  "en/enterprise/features/rbac"
+                  "en/enterprise/features/traces",
+                  "en/enterprise/features/hallucination-guardrail",
+                  "en/enterprise/features/integrations",
+                  "en/enterprise/features/agent-repositories"
                 ]
               },
               {
@@ -373,22 +333,6 @@
                   "en/enterprise/integrations/zendesk"
                 ]
               },
-              {
-                "group": "Triggers",
-                "pages": [
-                  "en/enterprise/guides/automation-triggers",
-                  "en/enterprise/guides/gmail-trigger",
-                  "en/enterprise/guides/google-calendar-trigger",
-                  "en/enterprise/guides/google-drive-trigger",
-                  "en/enterprise/guides/outlook-trigger",
-                  "en/enterprise/guides/onedrive-trigger",
-                  "en/enterprise/guides/microsoft-teams-trigger",
-                  "en/enterprise/guides/slack-trigger",
-                  "en/enterprise/guides/hubspot-trigger",
-                  "en/enterprise/guides/salesforce-trigger",
-                  "en/enterprise/guides/zapier-trigger"
-                ]
-              },
               {
                 "group": "How-To Guides",
                 "pages": [
@@ -398,11 +342,15 @@
                   "en/enterprise/guides/update-crew",
                   "en/enterprise/guides/enable-crew-studio",
                   "en/enterprise/guides/azure-openai-setup",
-                  "en/enterprise/guides/tool-repository",
+                  "en/enterprise/guides/automation-triggers",
+                  "en/enterprise/guides/hubspot-trigger",
                   "en/enterprise/guides/react-component-export",
+                  "en/enterprise/guides/salesforce-trigger",
+                  "en/enterprise/guides/slack-trigger",
                   "en/enterprise/guides/team-management",
+                  "en/enterprise/guides/webhook-automation",
                   "en/enterprise/guides/human-in-the-loop",
-                  "en/enterprise/guides/webhook-automation"
+                  "en/enterprise/guides/zapier-trigger"
                 ]
               },
               {
@@ -475,16 +423,6 @@
           ]
         },
         "tabs": [
-          {
-            "tab": "Início",
-            "icon": "house",
-            "groups": [
-              {
-                "group": "Bem-vindo",
-                "pages": ["pt-BR/index"]
-              }
-            ]
-          },
           {
             "tab": "Documentação",
             "icon": "book-open",
@@ -660,12 +598,12 @@
                     ]
                   },
                   {
-                    "group": "Integrations",
+                    "group": "Integrações",
                     "icon": "plug",
                     "pages": [
-                      "pt-BR/tools/integration/overview",
-                      "pt-BR/tools/integration/bedrockinvokeagenttool",
-                      "pt-BR/tools/integration/crewaiautomationtool"
+                      "pt-BR/tools/tool-integrations/overview",
+                      "pt-BR/tools/tool-integrations/bedrockinvokeagenttool",
+                      "pt-BR/tools/tool-integrations/crewaiautomationtool"
                     ]
                   },
                   {
@@ -685,7 +623,6 @@
                 "pages": [
                   "pt-BR/observability/overview",
                   "pt-BR/observability/arize-phoenix",
-                  "pt-BR/observability/braintrust",
                   "pt-BR/observability/langdb",
                   "pt-BR/observability/langfuse",
                   "pt-BR/observability/langtrace",
@@ -714,7 +651,6 @@
                   "pt-BR/learn/force-tool-output-as-result",
                   "pt-BR/learn/hierarchical-process",
                   "pt-BR/learn/human-input-on-execution",
-                  "pt-BR/learn/human-in-the-loop",
                   "pt-BR/learn/kickoff-async",
                   "pt-BR/learn/kickoff-for-each",
                   "pt-BR/learn/llm-connections",
@@ -731,7 +667,7 @@
             ]
           },
           {
-            "tab": "AMP",
+            "tab": "Enterprise",
             "icon": "briefcase",
             "groups": [
               {
@@ -739,27 +675,14 @@
                 "pages": ["pt-BR/enterprise/introduction"]
               },
               {
-                "group": "Construir",
+                "group": "Funcionalidades",
                 "pages": [
-                  "pt-BR/enterprise/features/automations",
-                  "pt-BR/enterprise/features/crew-studio",
-                  "pt-BR/enterprise/features/marketplace",
-                  "pt-BR/enterprise/features/agent-repositories",
-                  "pt-BR/enterprise/features/tools-and-integrations"
-                ]
-              },
-              {
-                "group": "Operar",
-                "pages": [
-                  "pt-BR/enterprise/features/traces",
+                  "pt-BR/enterprise/features/rbac",
+                  "pt-BR/enterprise/features/tool-repository",
                   "pt-BR/enterprise/features/webhook-streaming",
-                  "pt-BR/enterprise/features/hallucination-guardrail"
-                ]
-              },
-              {
-                "group": "Gerenciar",
-                "pages": [
-                  "pt-BR/enterprise/features/rbac"
+                  "pt-BR/enterprise/features/traces",
+                  "pt-BR/enterprise/features/hallucination-guardrail",
+                  "pt-BR/enterprise/features/integrations"
                 ]
               },
               {
@@ -792,20 +715,14 @@
                   "pt-BR/enterprise/guides/update-crew",
                   "pt-BR/enterprise/guides/enable-crew-studio",
                   "pt-BR/enterprise/guides/azure-openai-setup",
-                  "pt-BR/enterprise/guides/tool-repository",
-                  "pt-BR/enterprise/guides/react-component-export",
-                  "pt-BR/enterprise/guides/team-management",
-                  "pt-BR/enterprise/guides/human-in-the-loop",
-                  "pt-BR/enterprise/guides/webhook-automation"
-                ]
-              },
-              {
-                "group": "Triggers",
-                "pages": [
                   "pt-BR/enterprise/guides/automation-triggers",
-                  "pt-BR/enterprise/guides/slack-trigger",
                   "pt-BR/enterprise/guides/hubspot-trigger",
+                  "pt-BR/enterprise/guides/react-component-export",
                   "pt-BR/enterprise/guides/salesforce-trigger",
+                  "pt-BR/enterprise/guides/slack-trigger",
+                  "pt-BR/enterprise/guides/team-management",
+                  "pt-BR/enterprise/guides/webhook-automation",
+                  "pt-BR/enterprise/guides/human-in-the-loop",
                   "pt-BR/enterprise/guides/zapier-trigger"
                 ]
               },
@@ -881,16 +798,6 @@
           ]
         },
         "tabs": [
-          {
-            "tab": "홈",
-            "icon": "house",
-            "groups": [
-              {
-                "group": "환영합니다",
-                "pages": ["ko/index"]
-              }
-            ]
-          },
           {
             "tab": "기술 문서",
             "icon": "book-open",
@@ -1069,16 +976,17 @@
                       "ko/tools/cloud-storage/overview",
                       "ko/tools/cloud-storage/s3readertool",
                       "ko/tools/cloud-storage/s3writertool",
+                      "ko/tools/cloud-storage/bedrockinvokeagenttool",
                       "ko/tools/cloud-storage/bedrockkbretriever"
                     ]
                   },
                   {
-                    "group": "Integrations",
+                    "group": "통합",
                     "icon": "plug",
                     "pages": [
-                      "ko/tools/integration/overview",
-                      "ko/tools/integration/bedrockinvokeagenttool",
-                      "ko/tools/integration/crewaiautomationtool"
+                      "ko/tools/tool-integrations/overview",
+                      "ko/tools/tool-integrations/bedrockinvokeagenttool",
+                      "ko/tools/tool-integrations/crewaiautomationtool"
                     ]
                   },
                   {
@@ -1099,7 +1007,6 @@
                 "pages": [
                   "ko/observability/overview",
                   "ko/observability/arize-phoenix",
-                  "ko/observability/braintrust",
                   "ko/observability/langdb",
                   "ko/observability/langfuse",
                   "ko/observability/langtrace",
@@ -1128,7 +1035,6 @@
                   "ko/learn/force-tool-output-as-result",
                   "ko/learn/hierarchical-process",
                   "ko/learn/human-input-on-execution",
-                  "ko/learn/human-in-the-loop",
                   "ko/learn/kickoff-async",
                   "ko/learn/kickoff-for-each",
                   "ko/learn/llm-connections",
@@ -1153,27 +1059,15 @@
                 "pages": ["ko/enterprise/introduction"]
               },
               {
-                "group": "빌드",
+                "group": "특징",
                 "pages": [
-                  "ko/enterprise/features/automations",
-                  "ko/enterprise/features/crew-studio",
-                  "ko/enterprise/features/marketplace",
-                  "ko/enterprise/features/agent-repositories",
-                  "ko/enterprise/features/tools-and-integrations"
-                ]
-              },
-              {
-                "group": "운영",
-                "pages": [
-                  "ko/enterprise/features/traces",
+                  "ko/enterprise/features/rbac",
+                  "ko/enterprise/features/tool-repository",
                   "ko/enterprise/features/webhook-streaming",
-                  "ko/enterprise/features/hallucination-guardrail"
-                ]
-              },
-              {
-                "group": "관리",
-                "pages": [
-                  "ko/enterprise/features/rbac"
+                  "ko/enterprise/features/traces",
+                  "ko/enterprise/features/hallucination-guardrail",
+                  "ko/enterprise/features/integrations",
+                  "ko/enterprise/features/agent-repositories"
                 ]
               },
               {
@@ -1206,20 +1100,14 @@
                   "ko/enterprise/guides/update-crew",
                   "ko/enterprise/guides/enable-crew-studio",
                   "ko/enterprise/guides/azure-openai-setup",
-                  "ko/enterprise/guides/tool-repository",
-                  "ko/enterprise/guides/react-component-export",
-                  "ko/enterprise/guides/team-management",
-                  "ko/enterprise/guides/human-in-the-loop",
-                  "ko/enterprise/guides/webhook-automation"
-                ]
-              },
-              {
-                "group": "트리거",
-                "pages": [
                   "ko/enterprise/guides/automation-triggers",
-                  "ko/enterprise/guides/slack-trigger",
                   "ko/enterprise/guides/hubspot-trigger",
+                  "ko/enterprise/guides/react-component-export",
                   "ko/enterprise/guides/salesforce-trigger",
+                  "ko/enterprise/guides/slack-trigger",
+                  "ko/enterprise/guides/team-management",
+                  "ko/enterprise/guides/webhook-automation",
+                  "ko/enterprise/guides/human-in-the-loop",
                   "ko/enterprise/guides/zapier-trigger"
                 ]
               },

docs/en/api-reference/introduction.mdx

@@ -1,29 +1,29 @@
 ---
 title: "Introduction"
-description: "Complete reference for the CrewAI AMP REST API"
+description: "Complete reference for the CrewAI Enterprise REST API"
 icon: "code"
 mode: "wide"
 ---
 
-# CrewAI AMP API
+# CrewAI Enterprise API
 
-Welcome to the CrewAI AMP API reference. This API allows you to programmatically interact with your deployed crews, enabling integration with your applications, workflows, and services.
+Welcome to the CrewAI Enterprise API reference. This API allows you to programmatically interact with your deployed crews, enabling integration with your applications, workflows, and services.
 
 ## Quick Start
 
 <Steps>
   <Step title="Get Your API Credentials">
-    Navigate to your crew's detail page in the CrewAI AMP dashboard and copy your Bearer Token from the Status tab.
+    Navigate to your crew's detail page in the CrewAI Enterprise dashboard and copy your Bearer Token from the Status tab.
   </Step>
-
+  
   <Step title="Discover Required Inputs">
     Use the `GET /inputs` endpoint to see what parameters your crew expects.
   </Step>
-
+  
   <Step title="Start a Crew Execution">
     Call `POST /kickoff` with your inputs to start the crew execution and receive a `kickoff_id`.
   </Step>
-
+  
   <Step title="Monitor Progress">
     Use `GET /status/{kickoff_id}` to check execution status and retrieve results.
   </Step>
@@ -46,7 +46,7 @@ curl -H "Authorization: Bearer YOUR_CREW_TOKEN" \
 | **User Bearer Token** | User-scoped access | Limited permissions, suitable for user-specific operations |
 
 <Tip>
-You can find both token types in the Status tab of your crew's detail page in the CrewAI AMP dashboard.
+You can find both token types in the Status tab of your crew's detail page in the CrewAI Enterprise dashboard.
 </Tip>
 
 ## Base URL
@@ -62,7 +62,7 @@ Replace `your-crew-name` with your actual crew's URL from the dashboard.
 ## Typical Workflow
 
 1. **Discovery**: Call `GET /inputs` to understand what your crew needs
-2. **Execution**: Submit inputs via `POST /kickoff` to start processing
+2. **Execution**: Submit inputs via `POST /kickoff` to start processing  
 3. **Monitoring**: Poll `GET /status/{kickoff_id}` until completion
 4. **Results**: Extract the final output from the completed response
 
@@ -82,12 +82,12 @@ The API uses standard HTTP status codes:
 ## Interactive Testing
 
 <Info>
-**Why no "Send" button?** Since each CrewAI AMP user has their own unique crew URL, we use **reference mode** instead of an interactive playground to avoid confusion. This shows you exactly what the requests should look like without non-functional send buttons.
+**Why no "Send" button?** Since each CrewAI Enterprise user has their own unique crew URL, we use **reference mode** instead of an interactive playground to avoid confusion. This shows you exactly what the requests should look like without non-functional send buttons.
 </Info>
 
 Each endpoint page shows you:
 - ✅ **Exact request format** with all parameters
-- ✅ **Response examples** for success and error cases
+- ✅ **Response examples** for success and error cases  
 - ✅ **Code samples** in multiple languages (cURL, Python, JavaScript, etc.)
 - ✅ **Authentication examples** with proper Bearer token format
 
@@ -104,7 +104,7 @@ Each endpoint page shows you:
 
 **Example workflow:**
 1. **Copy this cURL example** from any endpoint page
-2. **Replace `your-actual-crew-name.crewai.com`** with your real crew URL
+2. **Replace `your-actual-crew-name.crewai.com`** with your real crew URL  
 3. **Replace the Bearer token** with your real token from the dashboard
 4. **Run the request** in your terminal or API client
 

docs/en/concepts/agents.mdx

@@ -20,7 +20,7 @@ Think of an agent as a specialized team member with specific skills, expertise,
 </Tip>
 
 <Note type="info" title="Enterprise Enhancement: Visual Agent Builder">
-CrewAI AMP includes a Visual Agent Builder that simplifies agent creation and configuration without writing code. Design your agents visually and test them in real-time.
+CrewAI Enterprise includes a Visual Agent Builder that simplifies agent creation and configuration without writing code. Design your agents visually and test them in real-time.
 
 ![Visual Agent Builder Screenshot](/images/enterprise/crew-studio-interface.png)
 

docs/en/concepts/cli.mdx

@@ -5,7 +5,7 @@ icon: terminal
 mode: "wide"
 ---
 
-<Warning>Since release 0.140.0, CrewAI AMP started a process of migrating their login provider. As such, the authentication flow via CLI was updated. Users that use Google to login, or that created their account after July 3rd, 2025 will be unable to log in with older versions of the `crewai` library.</Warning>
+<Warning>Since release 0.140.0, CrewAI Enterprise started a process of migrating their login provider. As such, the authentication flow via CLI was updated. Users that use Google to login, or that created their account after July 3rd, 2025 will be unable to log in with older versions of the `crewai` library.</Warning>
 
 ## Overview
 
@@ -186,9 +186,9 @@ def crew(self) -> Crew:
 
 ### 10. Deploy
 
-Deploy the crew or flow to [CrewAI AMP](https://app.crewai.com).
+Deploy the crew or flow to [CrewAI Enterprise](https://app.crewai.com).
 
-- **Authentication**: You need to be authenticated to deploy to CrewAI AMP.
+- **Authentication**: You need to be authenticated to deploy to CrewAI Enterprise.
     You can login or create an account with:
     ```shell Terminal
     crewai login
@@ -203,7 +203,7 @@ Deploy the crew or flow to [CrewAI AMP](https://app.crewai.com).
 
 ### 11. Organization Management
 
-Manage your CrewAI AMP organizations.
+Manage your CrewAI Enterprise organizations.
 
 ```shell Terminal
 crewai org [COMMAND] [OPTIONS]
@@ -227,17 +227,17 @@ crewai org switch <organization_id>
 ```
 
 <Note>
-You must be authenticated to CrewAI AMP to use these organization management commands.
+You must be authenticated to CrewAI Enterprise to use these organization management commands.
 </Note>
 
 - **Create a deployment** (continued):
     - Links the deployment to the corresponding remote GitHub repository (it usually detects this automatically).
 
-- **Deploy the Crew**: Once you are authenticated, you can deploy your crew or flow to CrewAI AMP.
+- **Deploy the Crew**: Once you are authenticated, you can deploy your crew or flow to CrewAI Enterprise.
     ```shell Terminal
     crewai deploy push
     ```
-    - Initiates the deployment process on the CrewAI AMP platform.
+    - Initiates the deployment process on the CrewAI Enterprise platform.
     - Upon successful initiation, it will output the Deployment created successfully! message along with the Deployment Name and a unique Deployment ID (UUID).
 
 - **Deployment Status**: You can check the status of your deployment with:
@@ -262,7 +262,7 @@ You must be authenticated to CrewAI AMP to use these organization management com
     ```shell Terminal
     crewai deploy remove
     ```
-    This deletes the deployment from the CrewAI AMP platform.
+    This deletes the deployment from the CrewAI Enterprise platform.
 
 - **Help Command**: You can get help with the CLI with:
     ```shell Terminal
@@ -270,20 +270,22 @@ You must be authenticated to CrewAI AMP to use these organization management com
     ```
     This shows the help message for the CrewAI Deploy CLI.
 
-Watch this video tutorial for a step-by-step demonstration of deploying your crew to [CrewAI AMP](http://app.crewai.com) using the CLI.
+Watch this video tutorial for a step-by-step demonstration of deploying your crew to [CrewAI Enterprise](http://app.crewai.com) using the CLI.
 
 <iframe
-  className="w-full aspect-video rounded-xl"
+  width="100%"
+  height="400"
   src="https://www.youtube.com/embed/3EqSV-CYDZA"
   title="CrewAI Deployment Guide"
-  frameBorder="0"
+  frameborder="0"
+  style={{ borderRadius: '10px' }}
   allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
-  allowFullScreen
+  allowfullscreen
 ></iframe>
 
 ### 11. Login
 
-Authenticate with CrewAI AMP using a secure device code flow (no email entry required).
+Authenticate with CrewAI Enterprise using a secure device code flow (no email entry required).
 
 ```shell Terminal
 crewai login
@@ -354,7 +356,7 @@ crewai config reset
 
 #### Available Configuration Parameters
 
-- `enterprise_base_url`: Base URL of the CrewAI AMP instance
+- `enterprise_base_url`: Base URL of the CrewAI Enterprise instance
 - `oauth2_provider`: OAuth2 provider used for authentication (e.g., workos, okta, auth0)
 - `oauth2_audience`: OAuth2 audience value, typically used to identify the target API or resource
 - `oauth2_client_id`: OAuth2 client ID issued by the provider, used during authentication requests
@@ -370,7 +372,7 @@ crewai config list
 Example output:
 | Setting             | Value                    | Description                                                 |
 | :------------------ | :----------------------- | :---------------------------------------------------------- |
-| enterprise_base_url | https://app.crewai.com   | Base URL of the CrewAI AMP instance                  |
+| enterprise_base_url | https://app.crewai.com   | Base URL of the CrewAI Enterprise instance                  |
 | org_name            | Not set                  | Name of the currently active organization                   |
 | org_uuid            | Not set                  | UUID of the currently active organization                   |
 | oauth2_provider     | workos                   | OAuth2 provider (e.g., workos, okta, auth0)                 |

docs/en/concepts/event-listener.mdx

@@ -20,7 +20,7 @@ CrewAI uses an event bus architecture to emit events throughout the execution li
 When specific actions occur in CrewAI (like a Crew starting execution, an Agent completing a task, or a tool being used), the system emits corresponding events. You can register handlers for these events to execute custom code when they occur.
 
 <Note type="info" title="Enterprise Enhancement: Prompt Tracing">
-CrewAI AMP provides a built-in Prompt Tracing feature that leverages the event system to track, store, and visualize all prompts, completions, and associated metadata. This provides powerful debugging capabilities and transparency into your agent operations.
+CrewAI Enterprise provides a built-in Prompt Tracing feature that leverages the event system to track, store, and visualize all prompts, completions, and associated metadata. This provides powerful debugging capabilities and transparency into your agent operations.
 
 ![Prompt Tracing Dashboard](/images/enterprise/traces-overview.png)
 

docs/en/concepts/flows.mdx

@@ -875,13 +875,14 @@ By exploring these examples, you can gain insights into how to leverage CrewAI F
 Also, check out our YouTube video on how to use flows in CrewAI below!
 
 <iframe
-  className="w-full aspect-video rounded-xl"
+  width="560"
+  height="315"
   src="https://www.youtube.com/embed/MTb5my6VOT8"
-  title="CrewAI Flows overview"
-  frameBorder="0"
+  title="YouTube video player"
+  frameborder="0"
   allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
-  referrerPolicy="strict-origin-when-cross-origin"
-  allowFullScreen
+  referrerpolicy="strict-origin-when-cross-origin"
+  allowfullscreen
 ></iframe>
 
 ## Running Flows

docs/en/concepts/tasks.mdx

@@ -14,7 +14,7 @@ Tasks provide all necessary details for execution, such as a description, the ag
 Tasks within CrewAI can be collaborative, requiring multiple agents to work together. This is managed through the task properties and orchestrated by the Crew's process, enhancing teamwork and efficiency.
 
 <Note type="info" title="Enterprise Enhancement: Visual Task Builder">
-CrewAI AMP includes a Visual Task Builder in Crew Studio that simplifies complex task creation and chaining. Design your task flows visually and test them in real-time without writing code.
+CrewAI Enterprise includes a Visual Task Builder in Crew Studio that simplifies complex task creation and chaining. Design your task flows visually and test them in real-time without writing code.
 
 ![Task Builder Screenshot](/images/enterprise/crew-studio-interface.png)
 
@@ -897,13 +897,14 @@ except RuntimeError as e:
 Check out the video below to see how to use structured outputs in CrewAI:
 
 <iframe
-  className="w-full aspect-video rounded-xl"
+  width="560"
+  height="315"
   src="https://www.youtube.com/embed/dNpKQk5uxHw"
-  title="Structured outputs in CrewAI"
-  frameBorder="0"
+  title="YouTube video player"
+  frameborder="0"
   allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
-  referrerPolicy="strict-origin-when-cross-origin"
-  allowFullScreen
+  referrerpolicy="strict-origin-when-cross-origin"
+  allowfullscreen
 ></iframe>
 
 ## Conclusion

docs/en/concepts/tools.mdx

@@ -17,7 +17,7 @@ This includes tools from the [CrewAI Toolkit](https://github.com/joaomdmoura/cre
 enabling everything from simple searches to complex interactions and effective teamwork among agents.
 
 <Note type="info" title="Enterprise Enhancement: Tools Repository">
-CrewAI AMP provides a comprehensive Tools Repository with pre-built integrations for common business systems and APIs. Deploy agents with enterprise tools in minutes instead of days.
+CrewAI Enterprise provides a comprehensive Tools Repository with pre-built integrations for common business systems and APIs. Deploy agents with enterprise tools in minutes instead of days.
 
 The Enterprise Tools Repository includes:
 - Pre-built connectors for popular enterprise systems
@@ -208,7 +208,7 @@ from crewai.tools import BaseTool
 class AsyncCustomTool(BaseTool):
     name: str = "async_custom_tool"
     description: str = "An asynchronous custom tool"
-
+    
     async def _run(self, query: str = "") -> str:
         """Asynchronously run the tool"""
         # Your async implementation here

docs/en/enterprise/features/agent-repositories.mdx

@@ -1,16 +1,12 @@
 ---
 title: 'Agent Repositories'
 description: 'Learn how to use Agent Repositories to share and reuse your agents across teams and projects'
-icon: 'people-group'
+icon: 'database'
 mode: "wide"
 ---
 
 Agent Repositories allow enterprise users to store, share, and reuse agent definitions across teams and projects. This feature enables organizations to maintain a centralized library of standardized agents, promoting consistency and reducing duplication of effort.
 
-<Frame>
-  ![Agent Repositories](/images/enterprise/agent-repositories.png)
-</Frame>
-
 ## Benefits of Agent Repositories
 
 - **Standardization**: Maintain consistent agent definitions across your organization
@@ -18,21 +14,25 @@ Agent Repositories allow enterprise users to store, share, and reuse agent defin
 - **Governance**: Implement organization-wide policies for agent configurations
 - **Collaboration**: Enable teams to share and build upon each other's work
 
-## Creating and Use Agent Repositories
+## Using Agent Repositories
+
+### Prerequisites
 
 1. You must have an account at CrewAI, try the [free plan](https://app.crewai.com).
-2. Create agents with specific roles and goals for your workflows.
-3. Configure tools and capabilities for each specialized assistant.
-4. Deploy agents across projects via visual interface or API integration.
+2. You need to be authenticated using the CrewAI CLI.
+3. If you have more than one organization, make sure you are switched to the correct organization using the CLI command:
 
-<Frame>
-  ![Agent Repositories](/images/enterprise/create-agent-repository.png)
-</Frame>
+```bash
+crewai org switch <org_id>
+```
 
+### Creating and Managing Agents in Repositories
+
+To create and manage agents in repositories,Enterprise Dashboard.
 
 ### Loading Agents from Repositories
 
-You can load agents from repositories in your code using the `from_repository` parameter to run locally:
+You can load agents from repositories in your code using the `from_repository` parameter:
 
 ```python
 from crewai import Agent
@@ -42,6 +42,7 @@ from crewai import Agent
 researcher = Agent(
     from_repository="market-research-agent"
 )
+
 ```
 
 ### Overriding Repository Settings

docs/en/enterprise/features/automations.mdx

@@ -1,104 +0,0 @@
----
-title: Automations
-description: "Manage, deploy, and monitor your live crews (automations) in one place."
-icon: "rocket"
-mode: "wide"
----
-
-## Overview
-
-Automations is the live operations hub for your deployed crews. Use it to deploy from GitHub or a ZIP file, manage environment variables, re‑deploy when needed, and monitor the status of each automation.
-
-<Frame>
-  ![Automations Overview](/images/enterprise/automations-overview.png)
-
-</Frame>
-
-## Deployment Methods
-
-### Deploy from GitHub
-
-Use this for version‑controlled projects and continuous deployment.
-
-<Steps>
-  <Step title="Connect GitHub">
-    Click <b>Configure GitHub</b> and authorize access.
-  </Step>
-  <Step title="Select Repository & Branch">
-    Choose the <b>Repository</b> and <b>Branch</b> you want to deploy from.
-  </Step>
-  <Step title="Enable Auto‑deploy (optional)">
-    Turn on <b>Automatically deploy new commits</b> to ship updates on every push.
-  </Step>
-  <Step title="Add Environment Variables">
-    Add secrets individually or use <b>Bulk View</b> for multiple variables.
-  </Step>
-  <Step title="Deploy">
-    Click <b>Deploy</b> to create your live automation.
-  </Step>
-</Steps>
-
-<Frame>
-  ![GitHub Deployment](/images/enterprise/deploy-from-github.png)
-</Frame>
-
-### Deploy from ZIP
-
-Ship quickly without Git—upload a compressed package of your project.
-
-<Steps>
-  <Step title="Choose File">
-    Select the ZIP archive from your computer.
-  </Step>
-  <Step title="Add Environment Variables">
-    Provide any required variables or keys.
-  </Step>
-  <Step title="Deploy">
-    Click <b>Deploy</b> to create your live automation.
-  </Step>
-</Steps>
-
-<Frame>
-  ![ZIP Deployment](/images/enterprise/deploy-from-zip.png)
-</Frame>
-
-## Automations Dashboard
-
-The table lists all live automations with key details:
-
-- **CREW**: Automation name
-- **STATUS**: Online / Failed / In Progress
-- **URL**: Endpoint for kickoff/status
-- **TOKEN**: Automation token
-- **ACTIONS**: Re‑deploy, delete, and more
-
-Use the top‑right controls to filter and search:
-
-- Search by name
-- Filter by <b>Status</b>
-- Filter by <b>Source</b> (GitHub / Studio / ZIP)
-
-Once deployed, you can view the automation details and have the **Options** dropdown menu to `chat with this crew`, `Export React Component` and `Export as MCP`.
-
-<Frame>
-  ![Automations Table](/images/enterprise/automations-table.png)
-</Frame>
-
-## Best Practices
-
-- Prefer GitHub deployments for version control and CI/CD
-- Use re‑deploy to roll forward after code or config updates or set it to auto-deploy on every push
-
-## Related
-
-<CardGroup cols={3}>
-  <Card title="Deploy a Crew" href="/en/enterprise/guides/deploy-crew" icon="rocket">
-    Deploy a Crew from GitHub or ZIP file.
-  </Card>
-  <Card title="Automation Triggers" href="/en/enterprise/guides/automation-triggers" icon="trigger">
-    Trigger automations via webhooks or API.
-  </Card>
-  <Card title="Webhook Automation" href="/en/enterprise/guides/webhook-automation" icon="webhook">
-    Stream real-time events and updates to your systems.
-  </Card>
-</CardGroup>

docs/en/enterprise/features/crew-studio.mdx

@@ -1,88 +0,0 @@
----
-title: Crew Studio
-description: "Build new automations with AI assistance, a visual editor, and integrated testing."
-icon: "pencil"
-mode: "wide"
----
-
-## Overview
-
-Crew Studio is an interactive, AI‑assisted workspace for creating new automations from scratch using natural language and a visual workflow editor.
-
-<Frame>
-  ![Crew Studio Overview](/images/enterprise/crew-studio-overview.png)
-</Frame>
-
-## Prompt‑based Creation
-
-- Describe the automation you want; the AI generates agents, tasks, and tools.
-- Use voice input via the microphone icon if preferred.
-- Start from built‑in prompts for common use cases.
-
-<Frame>
-  ![Prompt Builder](/images/enterprise/crew-studio-prompt.png)
-</Frame>
-
-## Visual Editor
-
-The canvas reflects the workflow as nodes and edges with three supporting panels that allow you to configure the workflow easily without writing code; a.k.a. "**vibe coding AI Agents**".
-
-You can use the drag-and-drop functionality to add agents, tasks, and tools to the canvas or you can use the chat section to build the agents. Both approaches share state and can be used interchangeably.
-
-- **AI Thoughts (left)**: streaming reasoning as the workflow is designed
-- **Canvas (center)**: agents and tasks as connected nodes
-- **Resources (right)**: drag‑and‑drop components (agents, tasks, tools)
-
-<Frame>
-  ![Visual Canvas](/images/enterprise/crew-studio-canvas.png)
-</Frame>
-
-## Execution & Debugging
-
-Switch to the <b>Execution</b> view to run and observe the workflow:
-
-- Event timeline
-- Detailed logs (Details, Messages, Raw Data)
-- Local test runs before publishing
-
-<Frame>
-  ![Execution View](/images/enterprise/crew-studio-execution.png)
-</Frame>
-
-## Publish & Export
-
-- <b>Publish</b> to deploy a live automation
-- <b>Download</b> source as a ZIP for local development or customization
-
-<Frame>
-  ![Publish & Download](/images/enterprise/crew-studio-publish.png)
-</Frame>
-
-Once published, you can view the automation details and have the **Options** dropdown menu to `chat with this crew`, `Export React Component` and `Export as MCP`.
-
-<Frame>
-  ![Published Automation](/images/enterprise/crew-studio-published.png)
-</Frame>
-
-## Best Practices
-
-- Iterate quickly in Studio; publish only when stable
-- Keep tools constrained to minimum permissions needed
-- Use Traces to validate behavior and performance
-
-## Related
-
-<CardGroup cols={4}>
-  <Card title="Enable Crew Studio" href="/en/enterprise/guides/enable-crew-studio" icon="palette">
-    Enable Crew Studio.
-  </Card>
-  <Card title="Build a Crew" href="/en/enterprise/guides/build-crew" icon="paintbrush">
-    Build a Crew.
-  </Card>
-  <Card title="Deploy a Crew" href="/en/enterprise/guides/deploy-crew" icon="rocket">
-    Deploy a Crew from GitHub or ZIP file.
-  </Card>
-  <Card title="Export a React Component" href="/en/enterprise/guides/react-component-export" icon="download">
-    Export a React Component.
-  </Card>
-</CardGroup>

docs/en/enterprise/features/integrations.mdx

@@ -0,0 +1,186 @@
+---
+title: Integrations
+description: "Connected applications for your agents to take actions."
+icon: "plug"
+mode: "wide"
+---
+
+## Overview
+
+Enable your agents to authenticate with any OAuth enabled provider and take actions. From Salesforce and HubSpot to Google and GitHub, we've got you covered with 16+ integrated services.
+
+<Frame>
+  ![Integrations](/images/enterprise/crew_connectors.png)
+</Frame>
+
+## Supported Integrations
+
+### **Communication & Collaboration**
+- **Gmail** - Manage emails and drafts
+- **Slack** - Workspace notifications and alerts
+- **Microsoft** - Office 365 and Teams integration
+
+### **Project Management**
+- **Jira** - Issue tracking and project management
+- **ClickUp** - Task and productivity management
+- **Asana** - Team task and project coordination
+- **Notion** - Page and database management
+- **Linear** - Software project and bug tracking
+- **GitHub** - Repository and issue management
+
+### **Customer Relationship Management**
+- **Salesforce** - CRM account and opportunity management
+- **HubSpot** - Sales pipeline and contact management
+- **Zendesk** - Customer support ticket management
+
+### **Business & Finance**
+- **Stripe** - Payment processing and customer management
+- **Shopify** - E-commerce store and product management
+
+### **Productivity & Storage**
+- **Google Sheets** - Spreadsheet data synchronization
+- **Google Calendar** - Event and schedule management
+- **Box** - File storage and document management
+
+and more to come!
+
+## Prerequisites
+
+Before using Authentication Integrations, ensure you have:
+
+- A [CrewAI Enterprise](https://app.crewai.com) account. You can get started with a free trial.
+
+
+## Setting Up Integrations
+
+### 1. Connect Your Account
+
+1. Navigate to [CrewAI Enterprise](https://app.crewai.com)
+2. Go to **Integrations** tab - https://app.crewai.com/crewai_plus/connectors
+3. Click **Connect** on your desired service from the Authentication Integrations section
+4. Complete the OAuth authentication flow
+5. Grant necessary permissions for your use case
+6. All set! Get your Enterprise Token from your [CrewAI Enterprise](https://app.crewai.com) in **Integration** tab
+
+<Frame>
+  ![Integrations](/images/enterprise/enterprise_action_auth_token.png)
+</Frame>
+
+### 2. Install Integration Tools
+
+All you need is the latest version of `crewai-tools` package.
+
+```bash
+uv add crewai-tools
+```
+
+## Usage Examples
+
+### Basic Usage
+<Tip>
+  All the services you are authenticated into will be available as tools. So all you need to do is add the `CrewaiEnterpriseTools` to your agent and you are good to go.
+</Tip>
+
+```python
+from crewai import Agent, Task, Crew
+from crewai_tools import CrewaiEnterpriseTools
+
+# Get enterprise tools (Gmail tool will be included)
+enterprise_tools = CrewaiEnterpriseTools(
+    enterprise_token="your_enterprise_token"
+)
+# print the tools
+print(enterprise_tools)
+
+# Create an agent with Gmail capabilities
+email_agent = Agent(
+    role="Email Manager",
+    goal="Manage and organize email communications",
+    backstory="An AI assistant specialized in email management and communication.",
+    tools=enterprise_tools
+)
+
+# Task to send an email
+email_task = Task(
+    description="Draft and send a follow-up email to john@example.com about the project update",
+    agent=email_agent,
+    expected_output="Confirmation that email was sent successfully"
+)
+
+# Run the task
+crew = Crew(
+    agents=[email_agent],
+    tasks=[email_task]
+)
+
+# Run the crew
+crew.kickoff()
+```
+
+### Filtering Tools
+
+```python
+from crewai_tools import CrewaiEnterpriseTools
+
+enterprise_tools = CrewaiEnterpriseTools(
+    actions_list=["gmail_find_email"] # only gmail_find_email tool will be available
+)
+gmail_tool = enterprise_tools["gmail_find_email"]
+
+gmail_agent = Agent(
+    role="Gmail Manager",
+    goal="Manage gmail communications and notifications",
+    backstory="An AI assistant that helps coordinate gmail communications.",
+    tools=[gmail_tool]
+)
+
+notification_task = Task(
+    description="Find the email from john@example.com",
+    agent=gmail_agent,
+    expected_output="Email found from john@example.com"
+)
+
+# Run the task
+crew = Crew(
+    agents=[slack_agent],
+    tasks=[notification_task]
+)
+```
+
+## Best Practices
+
+### Security
+- **Principle of Least Privilege**: Only grant the minimum permissions required for your agents' tasks
+- **Regular Audits**: Periodically review connected integrations and their permissions
+- **Secure Credentials**: Never hardcode credentials; use CrewAI's secure authentication flow
+
+
+### Filtering Tools
+On a deployed crew, you can specify which actions are avialbel for each integration from the settings page of the service you connected to.
+
+<Frame>
+  ![Integrations](/images/enterprise/filtering_enterprise_action_tools.png)
+</Frame>
+
+
+### Scoped Deployments for multi user organizations
+You can deploy your crew and scope each integration to a specific user. For example, a crew that connects to google can use a specific user's gmail account.
+
+<Tip>
+  This is useful for multi user organizations where you want to scope the integration to a specific user.
+</Tip>
+
+
+Use the `user_bearer_token` to scope the integration to a specific user so that when the crew is kicked off, it will use the user's bearer token to authenticate with the integration. If user is not logged in, then the crew will not use any connected integrations. Use the default bearer token to authenticate with the integrations thats deployed with the crew.
+
+<Frame>
+  ![Integrations](/images/enterprise/user_bearer_token.png)
+</Frame>
+
+
+
+### Getting Help
+
+<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
+  Contact our support team for assistance with integration setup or troubleshooting.
+</Card>

docs/en/enterprise/features/marketplace.mdx

@@ -1,46 +0,0 @@
----
-title: Marketplace
-description: "Discover, install, and govern reusable assets for your enterprise crews."
-icon: "store"
-mode: "wide"
----
-
-## Overview
-
-The Marketplace provides a curated surface for discovering integrations, internal tools, and reusable assets that accelerate crew development.
-
-<Frame>
-  ![Marketplace Overview](/images/enterprise/marketplace-overview.png)
-</Frame>
-
-## Discoverability
-
-- Browse by category and capability
-- Search for assets by name or keyword
-
-## Install & Enable
-
-- One‑click install for approved assets
-- Enable or disable per crew as needed
-- Configure required environment variables and scopes
-
-<Frame>
-  ![Install & Configure](/images/enterprise/marketplace-install.png)
-</Frame>
-
-You can also download the templates directly from the marketplace by clicking on the `Download` button so
-you can use them locally or refine them to your needs.
-
-## Related
-
-<CardGroup cols={3}>
-  <Card title="Tools & Integrations" href="/en/enterprise/features/tools-and-integrations" icon="wrench">
-    Connect external apps and manage internal tools your agents can use.
-  </Card>
-  <Card title="Tool Repository" href="/en/enterprise/features/tool-repository" icon="toolbox">
-    Publish and install tools to enhance your crews' capabilities.
-  </Card>
-  <Card title="Agents Repository" href="/en/enterprise/features/agent-repositories" icon="people-group">
-    Store, share, and reuse agent definitions across teams and projects.
-  </Card>
-</CardGroup>

docs/en/enterprise/features/rbac.mdx

@@ -7,16 +7,16 @@ mode: "wide"
 
 ## Overview
 
-RBAC in CrewAI AMP enables secure, scalable access management through a combination of organization‑level roles and automation‑level visibility controls.
+RBAC in CrewAI Enterprise enables secure, scalable access management through a combination of organization‑level roles and automation‑level visibility controls.
 
 <Frame>
-  <img src="/images/enterprise/users_and_roles.png" alt="RBAC overview in CrewAI AMP" />
-
+  <img src="/images/enterprise/users_and_roles.png" alt="RBAC overview in CrewAI Enterprise" />
+  
 </Frame>
 
 ## Users and Roles
 
-Each member in your CrewAI workspace is assigned a role, which determines their access across various features.
+Each member in your CrewAI workspace is assigned a role, which determines their access across various features. 
 
 You can:
 
@@ -28,7 +28,7 @@ You can configure users and roles in Settings → Roles.
 
 <Steps>
   <Step title="Open Roles settings">
-    Go to <b>Settings → Roles</b> in CrewAI AMP.
+    Go to <b>Settings → Roles</b> in CrewAI Enterprise.
   </Step>
   <Step title="Choose a role type">
     Use a predefined role (<b>Owner</b>, <b>Member</b>) or click <b>Create role</b> to define a custom one.
@@ -93,10 +93,12 @@ The organization owner always has access. In private mode, only whitelisted user
 </Tip>
 
 <Frame>
-  <img src="/images/enterprise/visibility.png" alt="Automation Visibility settings in CrewAI AMP" />
-
+  <img src="/images/enterprise/visibility.png" alt="Automation Visibility settings in CrewAI Enterprise" />
+  
 </Frame>
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
   Contact our support team for assistance with RBAC questions.
 </Card>
+
+

docs/en/enterprise/features/tool-repository.mdx

@@ -20,11 +20,11 @@ The repository is not a version control system. Use Git to track code changes an
 
 Before using the Tool Repository, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account
+- A [CrewAI Enterprise](https://app.crewai.com) account
 - [CrewAI CLI](https://docs.crewai.com/concepts/cli#cli) installed
 - uv>=0.5.0 installed. Check out [how to upgrade](https://docs.astral.sh/uv/getting-started/installation/#upgrading-uv)
 - [Git](https://git-scm.com) installed and configured
-- Access permissions to publish or install tools in your CrewAI AMP organization
+- Access permissions to publish or install tools in your CrewAI Enterprise organization
 
 ## Installing Tools
 
@@ -54,11 +54,11 @@ researcher = Agent(
 
 ## Adding other packages after installing a tool
 
-After installing a tool from the CrewAI AMP Tool Repository, you need to use the `crewai uv` command to add other packages to your project.
+After installing a tool from the CrewAI Enterprise Tool Repository, you need to use the `crewai uv` command to add other packages to your project.
 Using pure `uv` commands will fail due to authentication to tool repository being handled by the CLI. By using the `crewai uv` command, you can add other packages to your project without having to worry about authentication.
 Any `uv` command can be used with the `crewai uv` command, making it a powerful tool for managing your project's dependencies without the hassle of managing authentication through environment variables or other methods.
 
-Say that you have installed a custom tool from the CrewAI AMP Tool Repository called "my-tool":
+Say that you have installed a custom tool from the CrewAI Enterprise Tool Repository called "my-tool":
 
 ```bash
 crewai tool install my-tool
@@ -131,7 +131,7 @@ crewai tool publish
 
 To delete a tool:
 
-1. Go to [CrewAI AMP](https://app.crewai.com)
+1. Go to [CrewAI Enterprise](https://app.crewai.com)
 2. Navigate to **Tools**
 3. Select the tool
 4. Click **Delete**
@@ -142,14 +142,13 @@ Deletion is permanent. Deleted tools cannot be restored or re-installed.
 
 ## Security Checks
 
-Every published version undergoes automated security checks, and are only available to install after they pass.
+Every published version undergoes automated security checks, and are only available to install after they pass. 
 
 You can check the security check status of a tool at:
 
-`CrewAI AMP > Tools > Your Tool > Versions`
+`CrewAI Enterprise > Tools > Your Tool > Versions`
+
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
   Contact our support team for assistance with API integration or troubleshooting.
 </Card>
-
-

docs/en/enterprise/features/tools-and-integrations.mdx

@@ -1,249 +0,0 @@
----
-title: Tools & Integrations
-description: "Connect external apps and manage internal tools your agents can use."
-icon: "wrench"
-mode: "wide"
----
-
-## Overview
-
-Tools & Integrations is the central hub for connecting third‑party apps and managing internal tools that your agents can use at runtime.
-
-<Frame>
-  ![Tools & Integrations Overview](/images/enterprise/crew_connectors.png)
-</Frame>
-
-## Explore
-
-<Tabs>
-  <Tab title="Integrations" icon="plug">
-
-  ## Agent Apps (Integrations)
-
-  Connect enterprise‑grade applications (e.g., Gmail, Google Drive, HubSpot, Slack) via OAuth to enable agent actions.
-
-  <Steps>
-    <Step title="Connect">
-      Click <b>Connect</b> on an app and complete OAuth.
-    </Step>
-    <Step title="Configure">
-      Optionally adjust scopes, triggers, and action availability.
-    </Step>
-    <Step title="Use in Agents">
-      Connected services become available as tools for your agents.
-    </Step>
-  </Steps>
-
-  <Frame>
-    ![Integrations Grid](/images/enterprise/agent-apps.png)
-  </Frame>
-
-  ### Connect your Account
-
-  1. Go to <Link href="https://app.crewai.com/crewai_plus/connectors">Integrations</Link>
-  2. Click <b>Connect</b> on the desired service
-  3. Complete the OAuth flow and grant scopes
-  4. Copy your Enterprise Token from the <b>Integration</b> tab
-
-  <Frame>
-    ![Enterprise Token](/images/enterprise/enterprise_action_auth_token.png)
-  </Frame>
-
-  ### Install Integration Tools
-
-  To use the integrations locally, you need to install the latest `crewai-tools` package.
-
-  ```bash
-  uv add crewai-tools
-  ```
-
-  ### Usage Example
-
-  <Tip>
-    All services you have authenticated will be available as tools. Add `CrewaiEnterpriseTools` to your agent and you’re set.
-  </Tip>
-
-  ```python
-  from crewai import Agent, Task, Crew
-  from crewai_tools import CrewaiEnterpriseTools
-
-  # Get enterprise tools (Gmail tool will be included)
-  enterprise_tools = CrewaiEnterpriseTools(
-      enterprise_token="your_enterprise_token"
-  )
-  # print the tools
-  print(enterprise_tools)
-
-  # Create an agent with Gmail capabilities
-  email_agent = Agent(
-      role="Email Manager",
-      goal="Manage and organize email communications",
-      backstory="An AI assistant specialized in email management and communication.",
-      tools=enterprise_tools
-  )
-
-  # Task to send an email
-  email_task = Task(
-      description="Draft and send a follow-up email to john@example.com about the project update",
-      agent=email_agent,
-      expected_output="Confirmation that email was sent successfully"
-  )
-
-  # Run the task
-  crew = Crew(
-      agents=[email_agent],
-      tasks=[email_task]
-  )
-
-  # Run the crew
-  crew.kickoff()
-  ```
-
-  ### Filtering Tools
-
-  ```python
-  from crewai_tools import CrewaiEnterpriseTools
-
-  enterprise_tools = CrewaiEnterpriseTools(
-      actions_list=["gmail_find_email"]  # only gmail_find_email tool will be available
-  )
-
-
-  gmail_tool = enterprise_tools["gmail_find_email"]
-
-
-  gmail_agent = Agent(
-      role="Gmail Manager",
-      goal="Manage gmail communications and notifications",
-      backstory="An AI assistant that helps coordinate gmail communications.",
-      tools=[gmail_tool]
-  )
-
-  notification_task = Task(
-      description="Find the email from john@example.com",
-      agent=gmail_agent,
-      expected_output="Email found from john@example.com"
-  )
-
-  crew = Crew(
-      agents=[gmail_agent],
-      tasks=[notification_task]
-  )
-  ```
-
-  On a deployed crew, you can specify which actions are available for each integration from the service settings page.
-
-  <Frame>
-    ![Filter Actions](/images/enterprise/filtering_enterprise_action_tools.png)
-  </Frame>
-
-  ### Scoped Deployments (multi‑user orgs)
-
-  You can scope each integration to a specific user. For example, a crew that connects to Google can use a specific user’s Gmail account.
-
-  <Tip>
-    Useful when different teams/users must keep data access separated.
-  </Tip>
-
-  Use the `user_bearer_token` to scope authentication to the requesting user. If the user isn’t logged in, the crew won’t use connected integrations. Otherwise it falls back to the default bearer token configured for the deployment.
-
-  <Frame>
-    ![User Bearer Token](/images/enterprise/user_bearer_token.png)
-  </Frame>
-
-  <div id="catalog"></div>
-  ### Catalog
-
-  #### Communication & Collaboration
-  - Gmail — Manage emails and drafts
-  - Slack — Workspace notifications and alerts
-  - Microsoft — Office 365 and Teams integration
-
-  #### Project Management
-  - Jira — Issue tracking and project management
-  - ClickUp — Task and productivity management
-  - Asana — Team task and project coordination
-  - Notion — Page and database management
-  - Linear — Software project and bug tracking
-  - GitHub — Repository and issue management
-
-  #### Customer Relationship Management
-  - Salesforce — CRM account and opportunity management
-  - HubSpot — Sales pipeline and contact management
-  - Zendesk — Customer support ticket management
-
-  #### Business & Finance
-  - Stripe — Payment processing and customer management
-  - Shopify — E‑commerce store and product management
-
-  #### Productivity & Storage
-  - Google Sheets — Spreadsheet data synchronization
-  - Google Calendar — Event and schedule management
-  - Box — File storage and document management
-
-  …and more to come!
-
-  </Tab>
-  <Tab title="Internal Tools" icon="toolbox">
-
-  ## Internal Tools
-
-  Create custom tools locally, publish them on CrewAI AMP Tool Repository and use them in your agents.
-
-  <Tip>
-  Before running the commands below, make sure you log in to your CrewAI AMP account by running this command:
-    ```bash
-    crewai login
-    ```
-  </Tip>
-
-  <Frame>
-    ![Internal Tool Detail](/images/enterprise/tools-integrations-internal.png)
-  </Frame>
-
-  <Steps>
-    <Step title="Create">
-      Create a new tool locally.
-      ```bash
-      crewai tool create your-tool
-      ```
-    </Step>
-    <Step title="Publish">
-      Publish the tool to the CrewAI AMP Tool Repository.
-      ```bash
-      crewai tool publish
-      ```
-    </Step>
-    <Step title="Install">
-      Install the tool from the CrewAI AMP Tool Repository.
-      ```bash
-      crewai tool install your-tool
-      ```
-    </Step>
-  </Steps>
-
-  Manage:
-
-  - Name and description
-  - Visibility (Private / Public)
-  - Required environment variables
-  - Version history and downloads
-  - Team and role access
-
-  <Frame>
-    ![Internal Tool Detail](/images/enterprise/tool-configs.png)
-  </Frame>
-
-  </Tab>
-</Tabs>
-
-## Related
-
-<CardGroup cols={2}>
-  <Card title="Tool Repository" href="/en/enterprise/features/tool-repository" icon="toolbox">
-    Create, publish, and version custom tools for your organization.
-  </Card>
-  <Card title="Webhook Automation" href="/en/enterprise/guides/webhook-automation" icon="bolt">
-    Automate workflows and integrate with external platforms and services.
-  </Card>
-</CardGroup>

docs/en/enterprise/features/traces.mdx

@@ -11,7 +11,7 @@ Traces provide comprehensive visibility into your crew executions, helping you m
 
 ## What are Traces?
 
-Traces in CrewAI AMP are detailed execution records that capture every aspect of your crew's operation, from initial inputs to final outputs. They record:
+Traces in CrewAI Enterprise are detailed execution records that capture every aspect of your crew's operation, from initial inputs to final outputs. They record:
 
 - Agent thoughts and reasoning
 - Task execution details
@@ -28,9 +28,9 @@ Traces in CrewAI AMP are detailed execution records that capture every aspect of
 
 <Steps>
   <Step title="Navigate to the Traces Tab">
-    Once in your CrewAI AMP dashboard, click on the **Traces** to view all execution records.
+    Once in your CrewAI Enterprise dashboard, click on the **Traces** to view all execution records.
   </Step>
-
+  
   <Step title="Select an Execution">
     You'll see a list of all crew executions, sorted by date. Click on any execution to view its detailed trace.
   </Step>
@@ -112,7 +112,7 @@ Traces are invaluable for troubleshooting issues with your crews:
 <Steps>
   <Step title="Identify Failure Points">
     When a crew execution doesn't produce the expected results, examine the trace to find where things went wrong. Look for:
-
+    
     - Failed tasks
     - Unexpected agent decisions
     - Tool usage errors
@@ -122,19 +122,19 @@ Traces are invaluable for troubleshooting issues with your crews:
       ![Failure Points](/images/enterprise/failure.png)
     </Frame>
   </Step>
-
+  
   <Step title="Optimize Performance">
     Use execution metrics to identify performance bottlenecks:
-
+    
     - Tasks that took longer than expected
     - Excessive token usage
     - Redundant tool operations
     - Unnecessary API calls
   </Step>
-
+  
   <Step title="Improve Cost Efficiency">
     Analyze token usage and cost estimates to optimize your crew's efficiency:
-
+    
     - Consider using smaller models for simpler tasks
     - Refine prompts to be more concise
     - Cache frequently accessed information
@@ -153,5 +153,5 @@ CrewAI batches trace uploads to reduce overhead on high-volume runs:
 This yields more stable tracing under load while preserving detailed task/agent telemetry.
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with trace analysis or any other CrewAI AMP features.
-</Card>
+  Contact our support team for assistance with trace analysis or any other CrewAI Enterprise features.
+</Card>

docs/en/enterprise/features/webhook-streaming.mdx

@@ -7,8 +7,8 @@ mode: "wide"
 
 ## Overview
 
-Enterprise Event Streaming lets you receive real-time webhook updates about your crews and flows deployed to
-CrewAI AMP, such as model calls, tool usage, and flow steps.
+Enterprise Event Streaming lets you receive real-time webhook updates about your crews and flows deployed to 
+CrewAI Enterprise, such as model calls, tool usage, and flow steps.
 
 ## Usage
 
@@ -65,104 +65,99 @@ CrewAI supports both system events and custom events in Enterprise Event Streami
 
 ### Flow Events:
 
-  - `flow_created`
-  - `flow_started`
-  - `flow_finished`
-  - `flow_plot`
-  - `method_execution_started`
-  - `method_execution_finished`
-  - `method_execution_failed`
+  - flow_created
+  - flow_started
+  - flow_finished
+  - flow_plot
+  - method_execution_started
+  - method_execution_finished
+  - method_execution_failed
 
 ### Agent Events:
 
-  - `agent_execution_started`
-  - `agent_execution_completed`
-  - `agent_execution_error`
-  - `lite_agent_execution_started`
-  - `lite_agent_execution_completed`
-  - `lite_agent_execution_error`
-  - `agent_logs_started`
-  - `agent_logs_execution`
-  - `agent_evaluation_started`
-  - `agent_evaluation_completed`
-  - `agent_evaluation_failed`
+  - agent_execution_started
+  - agent_execution_completed
+  - agent_execution_error
+  - lite_agent_execution_started
+  - lite_agent_execution_completed
+  - lite_agent_execution_error
+  - agent_logs_started
+  - agent_logs_execution
+  - agent_evaluation_started
+  - agent_evaluation_completed
+  - agent_evaluation_failed
 
 ### Crew Events:
 
-  - `crew_kickoff_started`
-  - `crew_kickoff_completed`
-  - `crew_kickoff_failed`
-  - `crew_train_started`
-  - `crew_train_completed`
-  - `crew_train_failed`
-  - `crew_test_started`
-  - `crew_test_completed`
-  - `crew_test_failed`
-  - `crew_test_result`
+  - crew_kickoff_started
+  - crew_kickoff_completed
+  - crew_kickoff_failed
+  - crew_train_started
+  - crew_train_completed
+  - crew_train_failed
+  - crew_test_started
+  - crew_test_completed
+  - crew_test_failed
+  - crew_test_result
 
 ### Task Events:
 
-  - `task_started`
-  - `task_completed`
-  - `task_failed`
-  - `task_evaluation`
+  - task_started
+  - task_completed
+  - task_failed
+  - task_evaluation
 
 ### Tool Usage Events:
 
-  - `tool_usage_started`
-  - `tool_usage_finished`
-  - `tool_usage_error`
-  - `tool_validate_input_error`
-  - `tool_selection_error`
-  - `tool_execution_error`
+  - tool_usage_started
+  - tool_usage_finished
+  - tool_usage_error
+  - tool_validate_input_error
+  - tool_selection_error
+  - tool_execution_error
 
 ### LLM Events:
 
-  - `llm_call_started`
-  - `llm_call_completed`
-  - `llm_call_failed`
-  - `llm_stream_chunk`
+  - llm_call_started
+  - llm_call_completed
+  - llm_call_failed
+  - llm_stream_chunk
 
 ### LLM Guardrail Events:
 
-  - `llm_guardrail_started`
-  - `llm_guardrail_completed`
+  - llm_guardrail_started
+  - llm_guardrail_completed
 
 ### Memory Events:
 
-  - `memory_query_started`
-  - `memory_query_completed`
-  - `memory_query_failed`
-  - `memory_save_started`
-  - `memory_save_completed`
-  - `memory_save_failed`
-  - `memory_retrieval_started`
-  - `memory_retrieval_completed`
+  - memory_query_started
+  - memory_query_completed
+  - memory_query_failed
+  - memory_save_started
+  - memory_save_completed
+  - memory_save_failed
+  - memory_retrieval_started
+  - memory_retrieval_completed
 
 ### Knowledge Events:
 
-  - `knowledge_search_query_started`
-  - `knowledge_search_query_completed`
-  - `knowledge_search_query_failed`
-  - `knowledge_query_started`
-  - `knowledge_query_completed`
-  - `knowledge_query_failed`
+  - knowledge_search_query_started
+  - knowledge_search_query_completed
+  - knowledge_search_query_failed
+  - knowledge_query_started
+  - knowledge_query_completed
+  - knowledge_query_failed
 
 ### Reasoning Events:
 
-  - `agent_reasoning_started`
-  - `agent_reasoning_completed`
-  - `agent_reasoning_failed`
+  - agent_reasoning_started
+  - agent_reasoning_completed
+  - agent_reasoning_failed
 
-Event names match the internal event bus. See GitHub for the full list of events.
+Event names match the internal event bus. See [GitHub source](https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events) for the full list.
 
 You can emit your own custom events, and they will be delivered through the webhook stream alongside system events.
 
-<CardGroup>
- <Card title="GitHub" icon="github" href="https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events">
-  Full list of events
- </Card>
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
   Contact our support team for assistance with webhook integration or troubleshooting.
-</Card>
-</CardGroup>
+</Card>

docs/en/enterprise/guides/automation-triggers.mdx

@@ -1,72 +1,22 @@
 ---
-title: "Triggers Overview"
-description: "Understand how CrewAI AMP triggers work, how to manage them, and where to find integration-specific playbooks"
-icon: "face-smile"
+title: "Automation Triggers"
+description: "Automatically execute your CrewAI workflows when specific events occur in connected integrations"
+icon: "bolt"
 mode: "wide"
 ---
 
-CrewAI AMP triggers connect your automations to real-time events across the tools your teams already use. Instead of polling systems or relying on manual kickoffs, triggers listen for changes—new emails, calendar updates, CRM status changes—and immediately launch the crew or flow you specify.
+Automation triggers enable you to automatically run your CrewAI deployments when specific events occur in your connected integrations, creating powerful event-driven workflows that respond to real-time changes in your business systems.
 
-<Frame>
-  ![Automation Triggers Overview](/images/enterprise/crew_connectors.png)
-</Frame>
+## Overview
 
-### Integration Playbooks
-
-Deep-dive guides walk through setup and sample workflows for each integration:
-
-<CardGroup cols={2}>
-  <Card title="Gmail Trigger" icon="envelope">
-    <a href="/en/enterprise/guides/gmail-trigger">Enable crews when emails arrive or threads update.</a>
-  </Card>
-
-  <Card title="Google Calendar Trigger" icon="calendar-days">
-    <a href="/en/enterprise/guides/google-calendar-trigger">React to calendar events as they are created, updated, or cancelled.</a>
-  </Card>
-
-  <Card title="Google Drive Trigger" icon="folder-open">
-    <a href="/en/enterprise/guides/google-drive-trigger">Handle Drive file uploads, edits, and deletions.</a>
-  </Card>
-
-  <Card title="Outlook Trigger" icon="envelope-open">
-    <a href="/en/enterprise/guides/outlook-trigger">Automate responses to new Outlook messages and calendar updates.</a>
-  </Card>
-
-  <Card title="OneDrive Trigger" icon="cloud">
-    <a href="/en/enterprise/guides/onedrive-trigger">Audit file activity and sharing changes in OneDrive.</a>
-  </Card>
-
-  <Card title="Microsoft Teams Trigger" icon="comments">
-    <a href="/en/enterprise/guides/microsoft-teams-trigger">Kick off workflows when new Teams chats start.</a>
-  </Card>
-
-  <Card title="HubSpot Trigger" icon="hubspot">
-    <a href="/en/enterprise/guides/hubspot-trigger">Launch automations from HubSpot workflows and lifecycle events.</a>
-  </Card>
-
-  <Card title="Salesforce Trigger" icon="salesforce">
-    <a href="/en/enterprise/guides/salesforce-trigger">Connect Salesforce processes to CrewAI for CRM automation.</a>
-  </Card>
-
-  <Card title="Slack Trigger" icon="slack">
-    <a href="/en/enterprise/guides/slack-trigger">Start crews directly from Slack slash commands.</a>
-  </Card>
-
-  <Card title="Zapier Trigger" icon="bolt">
-    <a href="/en/enterprise/guides/zapier-trigger">Bridge CrewAI with thousands of Zapier-supported apps.</a>
-  </Card>
-</CardGroup>
-
-## Trigger Capabilities
-
-With triggers, you can:
+With automation triggers, you can:
 
 - **Respond to real-time events** - Automatically execute workflows when specific conditions are met
 - **Integrate with external systems** - Connect with platforms like Gmail, Outlook, OneDrive, JIRA, Slack, Stripe and more
 - **Scale your automation** - Handle high-volume events without manual intervention
 - **Maintain context** - Access trigger data within your crews and flows
 
-## Managing Triggers
+## Managing Automation Triggers
 
 ### Viewing Available Triggers
 
@@ -75,7 +25,7 @@ To access and manage your automation triggers:
 1. Navigate to your deployment in the CrewAI dashboard
 2. Click on the **Triggers** tab to view all available trigger integrations
 
-<Frame caption="Example of available automation triggers for a Gmail deployment">
+<Frame>
   <img src="/images/enterprise/list-available-triggers.png" alt="List of available automation triggers" />
 </Frame>
 
@@ -85,7 +35,7 @@ This view shows all the trigger integrations available for your deployment, alon
 
 Each trigger can be easily enabled or disabled using the toggle switch:
 
-<Frame caption="Enable or disable triggers with toggle">
+<Frame>
   <img src="/images/enterprise/trigger-selected.png" alt="Enable or disable triggers with toggle" />
 </Frame>
 
@@ -98,46 +48,24 @@ Simply click the toggle to change the trigger state. Changes take effect immedia
 
 Track the performance and history of your triggered executions:
 
-<Frame caption="List of executions triggered by automation">
+<Frame>
   <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
 </Frame>
 
-## Building Trigger-Driven Automations
+## Building Automation
 
 Before building your automation, it's helpful to understand the structure of trigger payloads that your crews and flows will receive.
 
-### Trigger Setup Checklist
+### Payload Samples Repository
 
-Before wiring a trigger into production, make sure you:
+We maintain a comprehensive repository with sample payloads from various trigger sources to help you build and test your automations:
 
-- Connect the integration under **Tools & Integrations** and complete any OAuth or API key steps
-- Enable the trigger toggle on the deployment that should respond to events
-- Provide any required environment variables (API tokens, tenant IDs, shared secrets)
-- Create or update tasks that can parse the incoming payload within the first crew task or flow step
-- Decide whether to pass trigger context automatically using `allow_crewai_trigger_context`
-- Set up monitoring—webhook logs, CrewAI execution history, and optional external alerting
-
-### Payload & Crew Examples Repository
-
-We maintain a comprehensive repository with end-to-end trigger examples to help you build and test your automations:
+**🔗 [CrewAI Enterprise Trigger Payload Samples](https://github.com/crewAIInc/crewai-enterprise-trigger-payload-samples)**
 
 This repository contains:
 
-- **Realistic payload samples** for every supported trigger integration
-- **Ready-to-run crew implementations** that parse each payload and turn it into a business workflow
-- **Multiple scenarios per integration** (e.g., new events, updates, deletions) so you can match the shape of your data
-
-| Integration | When it fires | Payload Samples | Crew Examples |
-| :-- | :-- | :-- | :-- |
-| Gmail | New messages, thread updates | [New alerts, thread updates](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/gmail) | [`new-email-crew.py`, `gmail-alert-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/gmail) |
-| Google Calendar | Event created / updated / started / ended / cancelled | [Event lifecycle payloads](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/google_calendar) | [`calendar-event-crew.py`, `calendar-meeting-crew.py`, `calendar-working-location-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/google_calendar) |
-| Google Drive | File created / updated / deleted | [File lifecycle payloads](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/google_drive) | [`drive-file-crew.py`, `drive-file-deletion-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/google_drive) |
-| Outlook | New email, calendar event removed | [Outlook payloads](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/outlook) | [`outlook-message-crew.py`, `outlook-event-removal-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/outlook) |
-| OneDrive | File operations (create, update, share, delete) | [OneDrive payloads](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/onedrive) | [`onedrive-file-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/onedrive) |
-| HubSpot | Record created / updated (contacts, companies, deals) | [HubSpot payloads](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/hubspot) | [`hubspot-company-crew.py`, `hubspot-contact-crew.py`, `hubspot-record-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/hubspot) |
-| Microsoft Teams | Chat thread created | [Teams chat payload](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/microsoft-teams) | [`teams-chat-created-crew.py`](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/microsoft-teams) |
-
-Use these samples to understand payload shape, copy the matching crew, and then replace the test payload with your live trigger data.
+- **Real payload examples** from different trigger sources (Gmail, Google Drive, etc.)
+- **Payload structure documentation** showing the format and available fields
 
 ### Triggers with Crew
 
@@ -249,7 +177,3 @@ def delegate_to_crew(self, crewai_trigger_payload: dict = None):
 - If you are developing, make sure the inputs include the `crewai_trigger_payload` parameter with the correct payload
 
 Automation triggers transform your CrewAI deployments into responsive, event-driven systems that can seamlessly integrate with your existing business processes and tools.
-
-<Card title="CrewAI AMP Trigger Examples" href="https://github.com/crewAIInc/crewai-enterprise-trigger-examples" icon="github">
-    Check them out on GitHub!
-</Card>

docs/en/enterprise/guides/azure-openai-setup.mdx

@@ -19,8 +19,8 @@ This guide walks you through connecting Azure OpenAI with Crew Studio for seamle
             </Frame>
     </Step>
 
-    <Step title="Configure CrewAI AMP Connection">
-        4. In another tab, open `CrewAI AMP > LLM Connections`. Name your LLM Connection, select Azure as the provider, and choose the same model you selected in Azure.
+    <Step title="Configure CrewAI Enterprise Connection">
+        4. In another tab, open `CrewAI Enterprise > LLM Connections`. Name your LLM Connection, select Azure as the provider, and choose the same model you selected in Azure.
         5. On the same page, add environment variables from step 3:
             - One named `AZURE_DEPLOYMENT_TARGET_URL` (using the Target URI). The URL should look like this: https://your-deployment.openai.azure.com/openai/deployments/gpt-4o/chat/completions?api-version=2024-08-01-preview
             - Another named `AZURE_API_KEY` (using the Key).
@@ -28,7 +28,7 @@ This guide walks you through connecting Azure OpenAI with Crew Studio for seamle
     </Step>
 
     <Step title="Set Default Configuration">
-        7. In `CrewAI AMP > Settings > Defaults > Crew Studio LLM Settings`, set the new LLM Connection and model as defaults.
+        7. In `CrewAI Enterprise > Settings > Defaults > Crew Studio LLM Settings`, set the new LLM Connection and model as defaults.
     </Step>
 
     <Step title="Configure Network Access">
@@ -49,4 +49,4 @@ If you encounter issues:
 - Verify the Target URI format matches the expected pattern
 - Check that the API key is correct and has proper permissions
 - Ensure network access is configured to allow CrewAI connections
-- Confirm the deployment model matches what you've configured in CrewAI
+- Confirm the deployment model matches what you've configured in CrewAI 

docs/en/enterprise/guides/build-crew.mdx

@@ -7,17 +7,19 @@ mode: "wide"
 
 ## Overview
 
-[CrewAI AMP](https://app.crewai.com) streamlines the process of **creating**, **deploying**, and **managing** your AI agents in production environments.
+[CrewAI Enterprise](https://app.crewai.com) streamlines the process of **creating**, **deploying**, and **managing** your AI agents in production environments.
 
 ## Getting Started
 
 <iframe
-  className="w-full aspect-video rounded-xl"
-  src="https://www.youtube.com/embed/-kSOTtYzgEw"
-  title="Building crews with the CrewAI CLI"
-  frameBorder="0"
-  allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
-  allowFullScreen
+    width="100%"
+    height="400"
+    src="https://www.youtube.com/embed/-kSOTtYzgEw"
+    title="Building Crews with CrewAI CLI"
+    frameborder="0"
+    style={{ borderRadius: '10px' }}
+    allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+    allowfullscreen
 ></iframe>
 
 ### Installation and Setup

docs/en/enterprise/guides/deploy-crew.mdx

@@ -1,12 +1,12 @@
 ---
 title: "Deploy Crew"
-description: "Deploying a Crew on CrewAI AMP"
+description: "Deploying a Crew on CrewAI Enterprise"
 icon: "rocket"
 mode: "wide"
 ---
 
 <Note>
-After creating a crew locally or through Crew Studio, the next step is deploying it to the CrewAI AMP platform. This guide covers multiple deployment methods to help you choose the best approach for your workflow.
+After creating a crew locally or through Crew Studio, the next step is deploying it to the CrewAI Enterprise platform. This guide covers multiple deployment methods to help you choose the best approach for your workflow.
 </Note>
 
 ## Prerequisites
@@ -39,10 +39,10 @@ The CLI provides the fastest way to deploy locally developed crews to the Enterp
   </Step>
 
   <Step title="Authenticate with the Enterprise Platform">
-    First, you need to authenticate your CLI with the CrewAI AMP platform:
+    First, you need to authenticate your CLI with the CrewAI Enterprise platform:
 
     ```bash
-    # If you already have a CrewAI AMP account, or want to create one:
+    # If you already have a CrewAI Enterprise account, or want to create one:
     crewai login
     ```
 
@@ -124,7 +124,7 @@ The CrewAI CLI offers several commands to manage your deployments:
 
 ## Option 2: Deploy Directly via Web Interface
 
-You can also deploy your crews directly through the CrewAI AMP web interface by connecting your GitHub account. This approach doesn't require using the CLI on your local machine.
+You can also deploy your crews directly through the CrewAI Enterprise web interface by connecting your GitHub account. This approach doesn't require using the CLI on your local machine.
 
 <Steps>
 
@@ -134,9 +134,9 @@ You can also deploy your crews directly through the CrewAI AMP web interface by
 
   </Step>
 
-  <Step title="Connecting GitHub to CrewAI AMP">
+  <Step title="Connecting GitHub to CrewAI Enterprise">
 
-    1. Log in to [CrewAI AMP](https://app.crewai.com)
+    1. Log in to [CrewAI Enterprise](https://app.crewai.com)
     2. Click on the button "Connect GitHub"
 
     <Frame>
@@ -190,7 +190,7 @@ You can also deploy your crews directly through the CrewAI AMP web interface by
 ## ⚠️ Environment Variable Security Requirements
 
 <Warning>
-**Important**: CrewAI AMP has security restrictions on environment variable names that can cause deployment failures if not followed.
+**Important**: CrewAI Enterprise has security restrictions on environment variable names that can cause deployment failures if not followed.
 </Warning>
 
 ### Blocked Environment Variable Patterns

docs/en/enterprise/guides/enable-crew-studio.mdx

@@ -1,17 +1,17 @@
 ---
 title: "Enable Crew Studio"
-description: "Enabling Crew Studio on CrewAI AMP"
+description: "Enabling Crew Studio on CrewAI Enterprise"
 icon: "comments"
 mode: "wide"
 ---
 
 <Tip>
-Crew Studio is a powerful **no-code/low-code** tool that allows you to quickly scaffold or build Crews through a conversational interface.
+Crew Studio is a powerful **no-code/low-code** tool that allows you to quickly scaffold or build Crews through a conversational interface. 
 </Tip>
 
 ## What is Crew Studio?
 
-Crew Studio is an innovative way to create AI agent crews without writing code.
+Crew Studio is an innovative way to create AI agent crews without writing code. 
 
 <Frame>
   ![Crew Studio Interface](/images/enterprise/crew-studio-interface.png)
@@ -24,7 +24,7 @@ With Crew Studio, you can:
 - Select appropriate tools
 - Configure necessary inputs
 - Generate downloadable code for customization
-- Deploy directly to the CrewAI AMP platform
+- Deploy directly to the CrewAI Enterprise platform
 
 ## Configuration Steps
 
@@ -32,14 +32,14 @@ Before you can start using Crew Studio, you need to configure your LLM connectio
 
 <Steps>
   <Step title="Set Up LLM Connection">
-    Go to the **LLM Connections** tab in your CrewAI AMP dashboard and create a new LLM connection.
+    Go to the **LLM Connections** tab in your CrewAI Enterprise dashboard and create a new LLM connection.
 
     <Note>
       Feel free to use any LLM provider you want that is supported by CrewAI.
     </Note>
-
+    
     Configure your LLM connection:
-
+    
     - Enter a `Connection Name` (e.g., `OpenAI`)
     - Select your model provider: `openai` or `azure`
     - Select models you'd like to use in your Studio-generated Crews
@@ -48,28 +48,28 @@ Before you can start using Crew Studio, you need to configure your LLM connectio
       - For OpenAI: Add `OPENAI_API_KEY` with your API key
       - For Azure OpenAI: Refer to [this article](https://blog.crewai.com/configuring-azure-openai-with-crewai-a-comprehensive-guide/) for configuration details
     - Click `Add Connection` to save your configuration
-
+    
     <Frame>
       ![LLM Connection Configuration](/images/enterprise/llm-connection-config.png)
     </Frame>
   </Step>
-
+  
   <Step title="Verify Connection Added">
     Once you complete the setup, you'll see your new connection added to the list of available connections.
-
+    
     <Frame>
       ![Connection Added](/images/enterprise/connection-added.png)
     </Frame>
   </Step>
-
+  
   <Step title="Configure LLM Defaults">
     In the main menu, go to **Settings → Defaults** and configure the LLM Defaults settings:
-
+    
     - Select default models for agents and other components
     - Set default configurations for Crew Studio
-
+    
     Click `Save Settings` to apply your changes.
-
+    
     <Frame>
       ![LLM Defaults Configuration](/images/enterprise/llm-defaults.png)
     </Frame>
@@ -82,38 +82,38 @@ Now that you've configured your LLM connection and default settings, you're read
 
 <Steps>
   <Step title="Access Studio">
-    Navigate to the **Studio** section in your CrewAI AMP dashboard.
+    Navigate to the **Studio** section in your CrewAI Enterprise dashboard.
   </Step>
-
+  
   <Step title="Start a Conversation">
     Start a conversation with the Crew Assistant by describing the problem you want to solve:
-
+    
     ```md
     I need a crew that can research the latest AI developments and create a summary report.
     ```
-
+    
     The Crew Assistant will ask clarifying questions to better understand your requirements.
   </Step>
-
+  
   <Step title="Review Generated Crew">
     Review the generated crew configuration, including:
-
+    
     - Agents and their roles
     - Tasks to be performed
     - Required inputs
     - Tools to be used
-
+    
     This is your opportunity to refine the configuration before proceeding.
   </Step>
-
+  
   <Step title="Deploy or Download">
     Once you're satisfied with the configuration, you can:
-
+    
     - Download the generated code for local customization
-    - Deploy the crew directly to the CrewAI AMP platform
+    - Deploy the crew directly to the CrewAI Enterprise platform
     - Modify the configuration and regenerate the crew
   </Step>
-
+  
   <Step title="Test Your Crew">
     After deployment, test your crew with sample inputs to ensure it performs as expected.
   </Step>
@@ -130,37 +130,38 @@ Here's a typical workflow for creating a crew with Crew Studio:
 <Steps>
   <Step title="Describe Your Problem">
     Start by describing your problem:
-
+    
     ```md
     I need a crew that can analyze financial news and provide investment recommendations
     ```
   </Step>
-
+  
   <Step title="Answer Questions">
     Respond to clarifying questions from the Crew Assistant to refine your requirements.
   </Step>
-
+  
   <Step title="Review the Plan">
     Review the generated crew plan, which might include:
-
+    
     - A Research Agent to gather financial news
     - An Analysis Agent to interpret the data
     - A Recommendations Agent to provide investment advice
   </Step>
-
+  
   <Step title="Approve or Modify">
     Approve the plan or request changes if necessary.
   </Step>
-
+  
   <Step title="Download or Deploy">
     Download the code for customization or deploy directly to the platform.
   </Step>
-
+  
   <Step title="Test and Refine">
     Test your crew with sample inputs and refine as needed.
   </Step>
 </Steps>
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Crew Studio or any other CrewAI AMP features.
+  Contact our support team for assistance with Crew Studio or any other CrewAI Enterprise features.
 </Card>
+

docs/en/enterprise/guides/gmail-trigger.mdx

@@ -1,85 +0,0 @@
----
-title: "Gmail Trigger"
-description: "Trigger automations when Gmail events occur (e.g., new emails, labels)."
-icon: "envelope"
-mode: "wide"
----
-
-## Overview
-
-Use the Gmail Trigger to kick off your deployed crews when Gmail events happen in connected accounts, such as receiving a new email or messages matching a label/filter.
-
-<Tip>
-  Make sure Gmail is connected in Tools & Integrations and the trigger is enabled for your deployment.
-</Tip>
-
-## Enabling the Gmail Trigger
-
-1. Open your deployment in CrewAI AMP
-2. Go to the **Triggers** tab
-3. Locate **Gmail** and switch the toggle to enable
-
-<Frame>
-  <img src="/images/enterprise/trigger-selected.png" alt="Enable or disable triggers with toggle" />
-</Frame>
-
-## Example: Process new emails
-
-When a new email arrives, the Gmail Trigger will send the payload to your Crew or Flow. Below is a Crew example that parses and processes the trigger payload.
-
-```python
-@CrewBase
-class GmailProcessingCrew:
-    @agent
-    def parser(self) -> Agent:
-        return Agent(
-            config=self.agents_config['parser'],
-        )
-
-    @task
-    def parse_gmail_payload(self) -> Task:
-        return Task(
-            config=self.tasks_config['parse_gmail_payload'],
-            agent=self.parser(),
-        )
-
-    @task
-    def act_on_email(self) -> Task:
-        return Task(
-            config=self.tasks_config['act_on_email'],
-            agent=self.parser(),
-        )
-```
-
-The Gmail payload will be available via the standard context mechanisms. See the payload samples repository for structure and fields.
-
-### Sample payloads & crews
-
-The [CrewAI AMP Trigger Examples repository](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/gmail) includes:
-
-- `new-email-payload-1.json` / `new-email-payload-2.json` — production-style new message alerts with matching crews in `new-email-crew.py`
-- `thread-updated-sample-1.json` — follow-up messages on an existing thread, processed by `gmail-alert-crew.py`
-
-Use these samples to validate your parsing logic locally before wiring the trigger to your live Gmail accounts.
-
-## Monitoring Executions
-
-Track history and performance of triggered runs:
-
-<Frame>
-  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
-</Frame>
-
-## Payload Reference
-
-See the sample payloads and field descriptions:
-
-<Card title="Gmail samples in Trigger Examples Repo" href="https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/gmail" icon="envelopes-bulk">
-    Gmail samples in Trigger Examples Repo
-</Card>
-
-## Troubleshooting
-
-- Ensure Gmail is connected in Tools & Integrations
-- Verify the Gmail Trigger is enabled on the Triggers tab
-- Check the execution logs and confirm the payload is passed as `crewai_trigger_payload`

docs/en/enterprise/guides/google-calendar-trigger.mdx

@@ -1,65 +0,0 @@
----
-title: "Google Calendar Trigger"
-description: "Kick off crews when Google Calendar events are created, updated, or cancelled"
-icon: "calendar"
-mode: "wide"
----
-
-## Overview
-
-Use the Google Calendar trigger to launch automations whenever calendar events change. Common use cases include briefing a team before a meeting, notifying stakeholders when a critical event is cancelled, or summarizing daily schedules.
-
-<Tip>
-  Make sure Google Calendar is connected in **Tools & Integrations** and enabled for the deployment you want to automate.
-</Tip>
-
-## Enabling the Google Calendar Trigger
-
-1. Open your deployment in CrewAI AMP
-2. Go to the **Triggers** tab
-3. Locate **Google Calendar** and switch the toggle to enable
-
-<Frame>
-  <img src="/images/enterprise/calendar-trigger.png" alt="Enable or disable triggers with toggle" />
-</Frame>
-
-## Example: Summarize meeting details
-
-The snippet below mirrors the `calendar-event-crew.py` example in the trigger repository. It parses the payload, analyses the attendees and timing, and produces a meeting brief for downstream tools.
-
-```python
-from calendar_event_crew import GoogleCalendarEventTrigger
-
-crew = GoogleCalendarEventTrigger().crew()
-result = crew.kickoff({
-    "crewai_trigger_payload": calendar_payload,
-})
-print(result.raw)
-```
-
-Use `crewai_trigger_payload` exactly as it is delivered by the trigger so the crew can extract the proper fields.
-
-## Sample payloads & crews
-
-The [Google Calendar examples](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/google_calendar) show how to handle multiple event types:
-
-- `new-event.json` → standard event creation handled by `calendar-event-crew.py`
-- `event-updated.json` / `event-started.json` / `event-ended.json` → in-flight updates processed by `calendar-meeting-crew.py`
-- `event-canceled.json` → cancellation workflow that alerts attendees via `calendar-meeting-crew.py`
-- Working location events use `calendar-working-location-crew.py` to extract on-site schedules
-
-Each crew transforms raw event metadata (attendees, rooms, working locations) into the summaries your teams need.
-
-## Monitoring Executions
-
-The **Executions** list in the deployment dashboard tracks every triggered run and surfaces payload metadata, output summaries, and errors.
-
-<Frame>
-  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
-</Frame>
-
-## Troubleshooting
-
-- Ensure the correct Google account is connected and the trigger is enabled
-- Confirm your workflow handles all-day events (payloads use `start.date` and `end.date` instead of timestamps)
-- Check execution logs if reminders or attendee arrays are missing—calendar permissions can limit fields in the payload

docs/en/enterprise/guides/google-drive-trigger.mdx

@@ -1,61 +0,0 @@
----
-title: "Google Drive Trigger"
-description: "Respond to Google Drive file events with automated crews"
-icon: "folder"
-mode: "wide"
----
-
-## Overview
-
-Trigger your automations when files are created, updated, or removed in Google Drive. Typical workflows include summarizing newly uploaded content, enforcing sharing policies, or notifying owners when critical files change.
-
-<Tip>
-  Connect Google Drive in **Tools & Integrations** and confirm the trigger is enabled for the automation you want to monitor.
-</Tip>
-
-## Enabling the Google Drive Trigger
-
-1. Open your deployment in CrewAI AMP
-2. Go to the **Triggers** tab
-3. Locate **Google Drive** and switch the toggle to enable
-
-<Frame>
-  <img src="/images/enterprise/gdrive-trigger.png" alt="Enable or disable triggers with toggle" />
-</Frame>
-
-## Example: Summarize file activity
-
-The drive example crews parse the payload to extract file metadata, evaluate permissions, and publish a summary.
-
-```python
-from drive_file_crew import GoogleDriveFileTrigger
-
-crew = GoogleDriveFileTrigger().crew()
-crew.kickoff({
-    "crewai_trigger_payload": drive_payload,
-})
-```
-
-## Sample payloads & crews
-
-Explore the [Google Drive examples](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/google_drive) to cover different operations:
-
-- `new-file.json` → new uploads processed by `drive-file-crew.py`
-- `updated-file.json` → file edits and metadata changes handled by `drive-file-crew.py`
-- `deleted-file.json` → deletion events routed through `drive-file-deletion-crew.py`
-
-Each crew highlights the file name, operation type, owner, permissions, and security considerations so downstream systems can respond appropriately.
-
-## Monitoring Executions
-
-Track history and performance of triggered runs with the **Executions** list in the deployment dashboard.
-
-<Frame>
-  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
-</Frame>
-
-## Troubleshooting
-
-- Verify Google Drive is connected and the trigger toggle is enabled
-- If a payload is missing permission data, ensure the connected account has access to the file or folder
-- The trigger sends file IDs only; use the Drive API if you need to fetch binary content during the crew run

docs/en/enterprise/guides/hubspot-trigger.mdx

@@ -5,22 +5,22 @@ icon: "hubspot"
 mode: "wide"
 ---
 
-This guide provides a step-by-step process to set up HubSpot triggers for CrewAI AMP, enabling you to initiate crews directly from HubSpot Workflows.
+This guide provides a step-by-step process to set up HubSpot triggers for CrewAI Enterprise, enabling you to initiate crews directly from HubSpot Workflows.
 
 ## Prerequisites
 
-- A CrewAI AMP account
+- A CrewAI Enterprise account
 - A HubSpot account with the [HubSpot Workflows](https://knowledge.hubspot.com/workflows/create-workflows) feature
 
 ## Setup Steps
 
 <Steps>
-    <Step title="Connect your HubSpot account with CrewAI AMP">
-        - Log in to your `CrewAI AMP account > Triggers`
+    <Step title="Connect your HubSpot account with CrewAI Enterprise">
+        - Log in to your `CrewAI Enterprise account > Triggers`
         - Select `HubSpot` from the list of available triggers
-        - Choose the HubSpot account you want to connect with CrewAI AMP
-        - Follow the on-screen prompts to authorize CrewAI AMP access to your HubSpot account
-        - A confirmation message will appear once HubSpot is successfully connected with CrewAI AMP
+        - Choose the HubSpot account you want to connect with CrewAI Enterprise
+        - Follow the on-screen prompts to authorize CrewAI Enterprise access to your HubSpot account
+        - A confirmation message will appear once HubSpot is successfully connected with CrewAI Enterprise
     </Step>
     <Step title="Create a HubSpot Workflow">
         - Log in to your `HubSpot account > Automations > Workflows > New workflow`
@@ -51,14 +51,4 @@ This guide provides a step-by-step process to set up HubSpot triggers for CrewAI
 
 ## Additional Resources
 
-### Sample payloads & crews
-
-You can jump-start development with the [HubSpot examples in the trigger repository](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/hubspot):
-
-- `record-created-contact.json`, `record-updated-contact.json` → contact lifecycle events handled by `hubspot-contact-crew.py`
-- `record-created-company.json`, `record-updated-company.json` → company enrichment flows in `hubspot-company-crew.py`
-- `record-created-deals.json`, `record-updated-deals.json` → deal pipeline automation in `hubspot-record-crew.py`
-
-Each crew demonstrates how to parse HubSpot record fields, enrich context, and return structured insights.
-
-For more detailed information on available actions and customization options, refer to the [HubSpot Workflows Documentation](https://knowledge.hubspot.com/workflows/create-workflows).
+For more detailed information on available actions and customization options, refer to the [HubSpot Workflows Documentation](https://knowledge.hubspot.com/workflows/create-workflows). 

docs/en/enterprise/guides/kickoff-crew.mdx

@@ -1,19 +1,19 @@
 ---
 title: "Kickoff Crew"
-description: "Kickoff a Crew on CrewAI AMP"
+description: "Kickoff a Crew on CrewAI Enterprise"
 icon: "flag-checkered"
 mode: "wide"
 ---
 
 ## Overview
 
-Once you've deployed your crew to the CrewAI AMP platform, you can kickoff executions through the web interface or the API. This guide covers both approaches.
+Once you've deployed your crew to the CrewAI Enterprise platform, you can kickoff executions through the web interface or the API. This guide covers both approaches.
 
 ## Method 1: Using the Web Interface
 
 ### Step 1: Navigate to Your Deployed Crew
 
-1. Log in to [CrewAI AMP](https://app.crewai.com)
+1. Log in to [CrewAI Enterprise](https://app.crewai.com)
 2. Click on the crew name from your projects list
 3. You'll be taken to the crew's detail page
 
@@ -83,7 +83,7 @@ Once execution is complete:
 
 ## Method 2: Using the API
 
-You can also kickoff crews programmatically using the CrewAI AMP REST API.
+You can also kickoff crews programmatically using the CrewAI Enterprise REST API.
 
 ### Authentication
 
@@ -184,3 +184,4 @@ If an execution fails:
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
   Contact our support team for assistance with execution issues or questions about the Enterprise platform.
 </Card>
+

docs/en/enterprise/guides/microsoft-teams-trigger.mdx

@@ -1,52 +0,0 @@
----
-title: "Microsoft Teams Trigger"
-description: "Kick off crews from Microsoft Teams chat activity"
-icon: "microsoft"
-mode: "wide"
----
-
-## Overview
-
-Use the Microsoft Teams trigger to start automations whenever a new chat is created. Common patterns include summarizing inbound requests, routing urgent messages to support teams, or creating follow-up tasks in other systems.
-
-<Tip>
-  Confirm Microsoft Teams is connected under **Tools & Integrations** and enabled in the **Triggers** tab for your deployment.
-</Tip>
-
-## Enabling the Microsoft Teams Trigger
-
-1. Open your deployment in CrewAI AMP
-2. Go to the **Triggers** tab
-3. Locate **Microsoft Teams** and switch the toggle to enable
-
-<Frame caption="Microsoft Teams trigger connection">
-  <img src="/images/enterprise/msteams-trigger.png" alt="Enable or disable triggers with toggle" />
-</Frame>
-
-## Example: Summarize a new chat thread
-
-```python
-from teams_chat_created_crew import MicrosoftTeamsChatTrigger
-
-crew = MicrosoftTeamsChatTrigger().crew()
-result = crew.kickoff({
-    "crewai_trigger_payload": teams_payload,
-})
-print(result.raw)
-```
-
-The crew parses thread metadata (subject, created time, roster) and generates an action plan for the receiving team.
-
-## Sample payloads & crews
-
-The [Microsoft Teams examples](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/microsoft-teams) include:
-
-- `chat-created.json` → chat creation payload processed by `teams-chat-created-crew.py`
-
-The crew demonstrates how to extract participants, initial messages, tenant information, and compliance metadata from the Microsoft Graph webhook payload.
-
-## Troubleshooting
-
-- Ensure the Teams connection is active; it must be refreshed if the tenant revokes permissions
-- Confirm the webhook subscription in Microsoft 365 is still valid if payloads stop arriving
-- Review execution logs for payload shape mismatches—Graph notifications may omit fields when a chat is private or restricted

docs/en/enterprise/guides/onedrive-trigger.mdx

@@ -1,53 +0,0 @@
----
-title: "OneDrive Trigger"
-description: "Automate responses to OneDrive file activity"
-icon: "cloud"
-mode: "wide"
----
-
-## Overview
-
-Start automations when files change inside OneDrive. You can generate audit summaries, notify security teams about external sharing, or update downstream line-of-business systems with new document metadata.
-
-<Tip>
-  Connect OneDrive in **Tools & Integrations** and toggle the trigger on for your deployment.
-</Tip>
-
-## Enabling the OneDrive Trigger
-
-1. Open your deployment in CrewAI AMP
-2. Go to the **Triggers** tab
-3. Locate **OneDrive** and switch the toggle to enable
-
-<Frame caption="Microsoft OneDrive trigger connection">
-  <img src="/images/enterprise/onedrive-trigger.png" alt="Enable or disable triggers with toggle" />
-</Frame>
-
-## Example: Audit file permissions
-
-```python
-from onedrive_file_crew import OneDriveFileTrigger
-
-crew = OneDriveFileTrigger().crew()
-crew.kickoff({
-    "crewai_trigger_payload": onedrive_payload,
-})
-```
-
-The crew inspects file metadata, user activity, and permission changes to produce a compliance-friendly summary.
-
-## Sample payloads & crews
-
-The [OneDrive examples](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/onedrive) showcase how to:
-
-- Parse file metadata, size, and folder paths
-- Track who created and last modified the file
-- Highlight permission and external sharing changes
-
-`onedrive-file-crew.py` bundles the analysis and summarization tasks so you can add remediation steps as needed.
-
-## Troubleshooting
-
-- Ensure the connected account has permission to read the file metadata included in the webhook
-- If the trigger fires but the payload is missing `permissions`, confirm the site-level sharing settings allow Graph to return this field
-- For large tenants, filter notifications upstream so the crew only runs on relevant directories

docs/en/enterprise/guides/outlook-trigger.mdx

@@ -1,52 +0,0 @@
----
-title: "Outlook Trigger"
-description: "Launch automations from Outlook emails and calendar updates"
-icon: "microsoft"
-mode: "wide"
----
-
-## Overview
-
-Automate responses when Outlook delivers a new message or when an event is removed from the calendar. Teams commonly route escalations, file tickets, or alert attendees of cancellations.
-
-<Tip>
-  Connect Outlook in **Tools & Integrations** and ensure the trigger is enabled for your deployment.
-</Tip>
-
-## Enabling the Outlook Trigger
-
-1. Open your deployment in CrewAI AMP
-2. Go to the **Triggers** tab
-3. Locate **Outlook** and switch the toggle to enable
-
-<Frame caption="Microsoft Outlook trigger connection">
-  <img src="/images/enterprise/outlook-trigger.png" alt="Enable or disable triggers with toggle" />
-</Frame>
-
-## Example: Summarize a new email
-
-```python
-from outlook_message_crew import OutlookMessageTrigger
-
-crew = OutlookMessageTrigger().crew()
-crew.kickoff({
-    "crewai_trigger_payload": outlook_payload,
-})
-```
-
-The crew extracts sender details, subject, body preview, and attachments before generating a structured response.
-
-## Sample payloads & crews
-
-Review the [Outlook examples](https://github.com/crewAIInc/crewai-enterprise-trigger-examples/tree/main/outlook) for two common scenarios:
-
-- `new-message.json` → new mail notifications parsed by `outlook-message-crew.py`
-- `event-removed.json` → calendar cleanup handled by `outlook-event-removal-crew.py`
-
-Each crew demonstrates how to handle Microsoft Graph payloads, normalize headers, and keep humans in-the-loop with concise summaries.
-
-## Troubleshooting
-
-- Verify the Outlook connector is still authorized; the subscription must be renewed periodically
-- If attachments are missing, confirm the webhook subscription includes the `includeResourceData` flag
-- Review execution logs when events fail to match—cancellation payloads lack attendee lists by design and the crew should account for that

docs/en/enterprise/guides/react-component-export.mdx

@@ -1,11 +1,11 @@
 ---
 title: "React Component Export"
-description: "Learn how to export and integrate CrewAI AMP React components into your applications"
+description: "Learn how to export and integrate CrewAI Enterprise React components into your applications"
 icon: "react"
 mode: "wide"
 ---
 
-This guide explains how to export CrewAI AMP crews as React components and integrate them into your own applications.
+This guide explains how to export CrewAI Enterprise crews as React components and integrate them into your own applications.
 
 ## Exporting a React Component
 
@@ -38,7 +38,7 @@ To run this React component locally, you'll need to set up a React development e
             npx create-react-app my-crew-app
             ```
         - Change into the project directory:
-
+        
             ```bash
             cd my-crew-app
             ```
@@ -77,7 +77,7 @@ To run this React component locally, you'll need to set up a React development e
 
     <Step title="Start the development server">
         - In your project directory, run:
-
+        
             ```bash
             npm start
             ```
@@ -101,4 +101,4 @@ You can then customise the `CrewLead.jsx` to add color, title etc
 - Customize the component styling to match your application's design
 - Add additional props for configuration
 - Integrate with your application's state management
-- Add error handling and loading states
+- Add error handling and loading states 

docs/en/enterprise/guides/salesforce-trigger.mdx

@@ -5,7 +5,7 @@ icon: "salesforce"
 mode: "wide"
 ---
 
-CrewAI AMP can be triggered from Salesforce to automate customer relationship management workflows and enhance your sales operations.
+CrewAI Enterprise can be triggered from Salesforce to automate customer relationship management workflows and enhance your sales operations.
 
 ## Overview
 
@@ -18,20 +18,15 @@ Salesforce is a leading customer relationship management (CRM) platform that hel
 
 ## Demo
 
-<iframe
-  className="w-full aspect-video rounded-xl"
-  src="https://www.youtube.com/embed/oJunVqjjfu4"
-  title="CrewAI + Salesforce trigger demo"
-  frameBorder="0"
-  allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
-  allowFullScreen
-></iframe>
+<Frame>
+    <iframe width="100%" height="400" src="https://www.youtube.com/embed/oJunVqjjfu4" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
+</Frame>
 
 ## Getting Started
 
 To set up Salesforce triggers:
 
-1. **Contact Support**: Reach out to CrewAI AMP support for assistance with Salesforce trigger setup
+1. **Contact Support**: Reach out to CrewAI Enterprise support for assistance with Salesforce trigger setup
 2. **Review Requirements**: Ensure you have the necessary Salesforce permissions and API access
 3. **Configure Connection**: Work with the support team to establish the connection between CrewAI and your Salesforce instance
 4. **Test Triggers**: Verify the triggers work correctly with your specific use cases
@@ -47,4 +42,4 @@ Common Salesforce + CrewAI trigger scenarios include:
 
 ## Next Steps
 
-For detailed setup instructions and advanced configuration options, please contact CrewAI AMP support who can provide tailored guidance for your specific Salesforce environment and business needs.
+For detailed setup instructions and advanced configuration options, please contact CrewAI Enterprise support who can provide tailored guidance for your specific Salesforce environment and business needs. 

docs/en/enterprise/guides/team-management.mdx

@@ -1,27 +1,27 @@
 ---
 title: "Team Management"
-description: "Learn how to invite and manage team members in your CrewAI AMP organization"
+description: "Learn how to invite and manage team members in your CrewAI Enterprise organization"
 icon: "users"
 mode: "wide"
 ---
 
-As an administrator of a CrewAI AMP account, you can easily invite new team members to join your organization. This guide will walk you through the process step-by-step.
+As an administrator of a CrewAI Enterprise account, you can easily invite new team members to join your organization. This guide will walk you through the process step-by-step.
 
 ## Inviting Team Members
 
 <Steps>
     <Step title="Access the Settings Page">
-        - Log in to your CrewAI AMP account
+        - Log in to your CrewAI Enterprise account
         - Look for the gear icon (⚙️) in the top right corner of the dashboard
         - Click on the gear icon to access the **Settings** page:
-            <Frame caption="Settings page">
+            <Frame>
                 <img src="/images/enterprise/settings-page.png" alt="Settings Page" />
             </Frame>
     </Step>
     <Step title="Navigate to the Members Section">
         - On the Settings page, you'll see a `Members` tab
         - Click on the `Members` tab to access the **Members** page:
-            <Frame caption="Members tab">
+            <Frame>
                 <img src="/images/enterprise/members-tab.png" alt="Members Tab" />
             </Frame>
     </Step>
@@ -43,7 +43,7 @@ You can add roles to your team members to control their access to different part
 
 <Steps>
     <Step title="Access the Settings Page">
-        - Log in to your CrewAI AMP account
+        - Log in to your CrewAI Enterprise account
         - Look for the gear icon (⚙️) in the top right corner of the dashboard
         - Click on the gear icon to access the **Settings** page:
             <Frame>
@@ -85,4 +85,4 @@ You can add roles to your team members to control their access to different part
 - **Invitation Acceptance**: Invited members will need to accept the invitation to join your organization
 - **Email Notifications**: You may want to inform your team members to check their email (including spam folders) for the invitation
 
-By following these steps, you can easily expand your team and collaborate more effectively within your CrewAI AMP organization.
+By following these steps, you can easily expand your team and collaborate more effectively within your CrewAI Enterprise organization. 

docs/en/enterprise/guides/update-crew.mdx

@@ -1,12 +1,12 @@
 ---
 title: "Update Crew"
-description: "Updating a Crew on CrewAI AMP"
+description: "Updating a Crew on CrewAI Enterprise"
 icon: "pencil"
 mode: "wide"
 ---
 
 <Note>
-After deploying your crew to CrewAI AMP, you may need to make updates to the code, security settings, or configuration.
+After deploying your crew to CrewAI Enterprise, you may need to make updates to the code, security settings, or configuration. 
 This guide explains how to perform these common update operations.
 </Note>
 
@@ -23,7 +23,7 @@ There are several reasons you might want to update your crew deployment:
 
 When you've pushed new commits to your GitHub repository and want to update your deployment:
 
-1. Navigate to your crew in the CrewAI AMP platform
+1. Navigate to your crew in the CrewAI Enterprise platform
 2. Click on the `Re-deploy` button on your crew details page
 
 <Frame>
@@ -36,7 +36,7 @@ This will trigger an update that you can track using the progress bar. The syste
 
 If you need to generate a new bearer token (for example, if you suspect the current token might have been compromised):
 
-1. Navigate to your crew in the CrewAI AMP platform
+1. Navigate to your crew in the CrewAI Enterprise platform
 2. Find the `Bearer Token` section
 3. Click the `Reset` button next to your current token
 
@@ -87,3 +87,4 @@ If you encounter any issues after updating, you can view deployment logs in the
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
   Contact our support team for assistance with updating your crew or troubleshooting deployment issues.
 </Card>
+

docs/en/enterprise/guides/webhook-automation.mdx

@@ -1,17 +1,17 @@
 ---
 title: "Webhook Automation"
-description: "Automate CrewAI AMP workflows using webhooks with platforms like ActivePieces, Zapier, and Make.com"
+description: "Automate CrewAI Enterprise workflows using webhooks with platforms like ActivePieces, Zapier, and Make.com"
 icon: "webhook"
 mode: "wide"
 ---
 
-CrewAI AMP allows you to automate your workflow using webhooks. This article will guide you through the process of setting up and using webhooks to kickoff your crew execution, with a focus on integration with ActivePieces, a workflow automation platform similar to Zapier and Make.com.
+CrewAI Enterprise allows you to automate your workflow using webhooks. This article will guide you through the process of setting up and using webhooks to kickoff your crew execution, with a focus on integration with ActivePieces, a workflow automation platform similar to Zapier and Make.com.
 
 ## Setting Up Webhooks
 
 <Steps>
     <Step title="Accessing the Kickoff Interface">
-        - Navigate to the CrewAI AMP dashboard
+        - Navigate to the CrewAI Enterprise dashboard
         - Look for the `/kickoff` section, which is used to start the crew execution
             <Frame>
                 <img src="/images/enterprise/kickoff-interface.png" alt="Kickoff Interface" />
@@ -44,7 +44,7 @@ CrewAI AMP allows you to automate your workflow using webhooks. This article wil
         3. Add an HTTP action step
             - Set the action to `Send HTTP request`
             - Use `POST` as the method
-            - Set the URL to your CrewAI AMP kickoff endpoint
+            - Set the URL to your CrewAI Enterprise kickoff endpoint
             - Add necessary headers (e.g., `Bearer Token`)
                 <Frame>
                     <img src="/images/enterprise/activepieces-headers.png" alt="ActivePieces Headers" />
@@ -59,7 +59,7 @@ CrewAI AMP allows you to automate your workflow using webhooks. This article wil
     </Step>
 
     <Step title="Setting Up the Webhook">
-        1. Create a new flow in ActivePieces and name it
+        1. Create a new flow in ActivePieces and name it 
             <Frame>
                 <img src="/images/enterprise/activepieces-flow.png" alt="ActivePieces Flow" />
             </Frame>
@@ -152,4 +152,4 @@ CrewAI AMP allows you to automate your workflow using webhooks. This article wil
         }
         ```
     </Tab>
-</Tabs>
+</Tabs> 

docs/en/enterprise/guides/zapier-trigger.mdx

@@ -5,11 +5,11 @@ icon: "bolt"
 mode: "wide"
 ---
 
-This guide will walk you through the process of setting up Zapier triggers for CrewAI AMP, allowing you to automate workflows between CrewAI AMP and other applications.
+This guide will walk you through the process of setting up Zapier triggers for CrewAI Enterprise, allowing you to automate workflows between CrewAI Enterprise and other applications.
 
 ## Prerequisites
 
-- A CrewAI AMP account
+- A CrewAI Enterprise account
 - A Zapier account
 - A Slack account (for this specific example)
 
@@ -32,7 +32,7 @@ This guide will walk you through the process of setting up Zapier triggers for C
         - Connect your Slack account if you haven't already.
     </Step>
 
-    <Step title="Configure the CrewAI AMP Action">
+    <Step title="Configure the CrewAI Enterprise Action">
         - Add a new action step to your Zap.
         - Choose CrewAI+ as your action app and Kickoff as the Action Event
 
@@ -41,8 +41,8 @@ This guide will walk you through the process of setting up Zapier triggers for C
         </Frame>
     </Step>
 
-    <Step title="Connect your CrewAI AMP account">
-        - Connect your CrewAI AMP account.
+    <Step title="Connect your CrewAI Enterprise account">
+        - Connect your CrewAI Enterprise account.
         - Select the appropriate Crew for your workflow.
 
         <Frame>
@@ -51,8 +51,8 @@ This guide will walk you through the process of setting up Zapier triggers for C
         - Configure the inputs for the Crew using the data from the Slack message.
     </Step>
 
-    <Step title="Format the CrewAI AMP Output">
-        - Add another action step to format the text output from CrewAI AMP.
+    <Step title="Format the CrewAI Enterprise Output">
+        - Add another action step to format the text output from CrewAI Enterprise.
         - Use Zapier's formatting tools to convert the Markdown output to HTML.
 
         <Frame>
@@ -67,7 +67,7 @@ This guide will walk you through the process of setting up Zapier triggers for C
         - Add a final action step to send the formatted output via email.
         - Choose your preferred email service (e.g., Gmail, Outlook).
         - Configure the email details, including recipient, subject, and body.
-        - Insert the formatted CrewAI AMP output into the email body.
+        - Insert the formatted CrewAI Enterprise output into the email body.
 
         <Frame>
             <img src="/images/enterprise/zapier-7.png" alt="Zapier 7" />
@@ -97,8 +97,8 @@ This guide will walk you through the process of setting up Zapier triggers for C
 
 ## Tips for Success
 
-- Ensure that your CrewAI AMP inputs are correctly mapped from the Slack message.
+- Ensure that your CrewAI Enterprise inputs are correctly mapped from the Slack message.
 - Test your Zap thoroughly before turning it on to catch any potential issues.
 - Consider adding error handling steps to manage potential failures in the workflow.
 
-By following these steps, you'll have successfully set up Zapier triggers for CrewAI AMP, allowing for automated workflows triggered by Slack messages and resulting in email notifications with CrewAI AMP output.
+By following these steps, you'll have successfully set up Zapier triggers for CrewAI Enterprise, allowing for automated workflows triggered by Slack messages and resulting in email notifications with CrewAI Enterprise output. 

docs/en/enterprise/integrations/asana.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage tasks, projects, and team coordination through Asan
 
 Before using the Asana integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - An Asana account with appropriate permissions
 - Connected your Asana account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Asana integration, ensure you have:
 
 ### 1. Connect Your Asana Account
 
-1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI Enterprise Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Asana** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for task and project management

docs/en/enterprise/integrations/box.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage files, folders, and documents through Box. Upload f
 
 Before using the Box integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A Box account with appropriate permissions
 - Connected your Box account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Box integration, ensure you have:
 
 ### 1. Connect Your Box Account
 
-1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI Enterprise Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Box** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for file and folder management

docs/en/enterprise/integrations/clickup.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage tasks, projects, and productivity workflows through
 
 Before using the ClickUp integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A ClickUp account with appropriate permissions
 - Connected your ClickUp account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the ClickUp integration, ensure you have:
 
 ### 1. Connect Your ClickUp Account
 
-1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI Enterprise Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **ClickUp** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for task and project management

docs/en/enterprise/integrations/github.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage repositories, issues, and releases through GitHub.
 
 Before using the GitHub integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A GitHub account with appropriate repository permissions
 - Connected your GitHub account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the GitHub integration, ensure you have:
 
 ### 1. Connect Your GitHub Account
 
-1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI Enterprise Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **GitHub** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for repository and issue management

docs/en/enterprise/integrations/gmail.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage emails, contacts, and drafts through Gmail. Send em
 
 Before using the Gmail integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A Gmail account with appropriate permissions
 - Connected your Gmail account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Gmail integration, ensure you have:
 
 ### 1. Connect Your Gmail Account
 
-1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI Enterprise Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Gmail** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for email and contact management

docs/en/enterprise/integrations/google_calendar.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage calendar events, schedules, and availability throug
 
 Before using the Google Calendar integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A Google account with Google Calendar access
 - Connected your Google account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Google Calendar integration, ensure you have:
 
 ### 1. Connect Your Google Account
 
-1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI Enterprise Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Google Calendar** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for calendar and contact access

docs/en/enterprise/integrations/google_sheets.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage spreadsheet data through Google Sheets. Read rows,
 
 Before using the Google Sheets integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A Google account with Google Sheets access
 - Connected your Google account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 - Spreadsheets with proper column headers for data operations
@@ -22,7 +22,7 @@ Before using the Google Sheets integration, ensure you have:
 
 ### 1. Connect Your Google Account
 
-1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI Enterprise Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Google Sheets** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for spreadsheet access

docs/en/enterprise/integrations/hubspot.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage companies and contacts within HubSpot. Create new r
 
 Before using the HubSpot integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription.
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription.
 - A HubSpot account with appropriate permissions.
 - Connected your HubSpot account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors).
 
@@ -21,7 +21,7 @@ Before using the HubSpot integration, ensure you have:
 
 ### 1. Connect Your HubSpot Account
 
-1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors).
+1. Navigate to [CrewAI Enterprise Integrations](https://app.crewai.com/crewai_plus/connectors).
 2. Find **HubSpot** in the Authentication Integrations section.
 3. Click **Connect** and complete the OAuth flow.
 4. Grant the necessary permissions for company and contact management.

docs/en/enterprise/integrations/jira.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage issues, projects, and workflows through Jira. Creat
 
 Before using the Jira integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A Jira account with appropriate project permissions
 - Connected your Jira account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Jira integration, ensure you have:
 
 ### 1. Connect Your Jira Account
 
-1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI Enterprise Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Jira** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for issue and project management

docs/en/enterprise/integrations/linear.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage issues, projects, and development workflows through
 
 Before using the Linear integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A Linear account with appropriate workspace permissions
 - Connected your Linear account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Linear integration, ensure you have:
 
 ### 1. Connect Your Linear Account
 
-1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI Enterprise Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Linear** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for issue and project management

docs/en/enterprise/integrations/notion.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage pages, databases, and content through Notion. Creat
 
 Before using the Notion integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A Notion account with appropriate workspace permissions
 - Connected your Notion account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Notion integration, ensure you have:
 
 ### 1. Connect Your Notion Account
 
-1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI Enterprise Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Notion** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for page and database management

docs/en/enterprise/integrations/salesforce.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage customer relationships, sales processes, and data t
 
 Before using the Salesforce integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A Salesforce account with appropriate permissions
 - Connected your Salesforce account through the [Integrations page](https://app.crewai.com/integrations)
 

docs/en/enterprise/integrations/shopify.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage e-commerce operations through Shopify. Handle custo
 
 Before using the Shopify integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A Shopify store with appropriate admin permissions
 - Connected your Shopify store through the [Integrations page](https://app.crewai.com/integrations)
 

docs/en/enterprise/integrations/slack.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage team communication through Slack. Send messages, se
 
 Before using the Slack integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A Slack workspace with appropriate permissions
 - Connected your Slack workspace through the [Integrations page](https://app.crewai.com/integrations)
 

docs/en/enterprise/integrations/stripe.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage payments, subscriptions, and customer billing throu
 
 Before using the Stripe integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A Stripe account with appropriate API permissions
 - Connected your Stripe account through the [Integrations page](https://app.crewai.com/integrations)
 

docs/en/enterprise/integrations/zendesk.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage customer support operations through Zendesk. Create
 
 Before using the Zendesk integration, ensure you have:
 
-- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A [CrewAI Enterprise](https://app.crewai.com) account with an active subscription
 - A Zendesk account with appropriate API permissions
 - Connected your Zendesk account through the [Integrations page](https://app.crewai.com/integrations)
 

docs/en/enterprise/introduction.mdx

@@ -1,5 +1,5 @@
 ---
-title: "CrewAI AMP"
+title: "CrewAI Enterprise"
 description: "Deploy, monitor, and scale your AI agent workflows"
 icon: "globe"
 mode: "wide"
@@ -7,13 +7,13 @@ mode: "wide"
 
 ## Introduction
 
-CrewAI AMP(Agent Management Platform) provides a platform for deploying, monitoring, and scaling your crews and agents in a production environment.
+CrewAI Enterprise provides a platform for deploying, monitoring, and scaling your crews and agents in a production environment.
 
 <Frame>
-  <img src="/images/enterprise/crewai-enterprise-dashboard.png" alt="CrewAI AMP Dashboard" />
+  <img src="/images/enterprise/crewai-enterprise-dashboard.png" alt="CrewAI Enterprise Dashboard" />
 </Frame>
 
-CrewAI AMP extends the power of the open-source framework with features designed for production deployments, collaboration, and scalability. Deploy your crews to a managed infrastructure and monitor their execution in real-time.
+CrewAI Enterprise extends the power of the open-source framework with features designed for production deployments, collaboration, and scalability. Deploy your crews to a managed infrastructure and monitor their execution in real-time.
 
 ## Key Features
 

docs/en/enterprise/resources/frequently-asked-questions.mdx

@@ -1,6 +1,6 @@
 ---
 title: FAQs
-description: "Frequently asked questions about CrewAI AMP"
+description: "Frequently asked questions about CrewAI Enterprise"
 icon: "circle-question"
 mode: "wide"
 ---
@@ -129,14 +129,15 @@ mode: "wide"
         </Steps>
 
         Here's a tutorial on how to consistently get structured outputs from your agents:
-        <iframe
-          className="w-full aspect-video rounded-xl"
-          src="https://www.youtube.com/embed/dNpKQk5uxHw"
-          title="Structured outputs in CrewAI"
-          frameBorder="0"
-          allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
-          allowFullScreen
-        ></iframe>
+        <Frame>
+            <iframe
+            height="400"
+            width="100%"
+            src="https://www.youtube.com/embed/dNpKQk5uxHw"
+            title="YouTube video player" frameborder="0"
+            allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+            allowfullscreen></iframe>
+        </Frame>
     </Accordion>
 
     <Accordion title="How can I create custom tools for my CrewAI agents?">

docs/en/examples/cookbooks.mdx

@@ -7,43 +7,17 @@ mode: "wide"
 
 ## Quickstarts & Demos
 
-<CardGroup cols={3}>
-  <Card title="Collaboration" icon="people-arrows" href="https://github.com/crewAIInc/crewAI-quickstarts/blob/main/Collaboration/crewai_collaboration.ipynb">
-    Coordinate multiple agents on shared tasks. Includes notebook with end-to-end collaboration pattern.
-  </Card>
-
-  <Card title="Planning" icon="timeline" href="https://github.com/crewAIInc/crewAI-quickstarts/blob/main/Planning/crewai_planning.ipynb">
-    Teach agents to reason about multi-step plans before execution using the planning toolkit.
-  </Card>
-
-  <Card title="Reasoning" icon="lightbulb" href="https://github.com/crewAIInc/crewAI-quickstarts/blob/main/Reasoning/crewai_reasoning.ipynb">
-    Explore self-reflection loops, critique prompts, and structured thinking patterns.
-  </Card>
-</CardGroup>
-
-<CardGroup cols={3}>
-  <Card title="Structured Guardrails" icon="shield-check" href="https://github.com/crewAIInc/crewAI-quickstarts/blob/main/Guardrails/task_guardrails.ipynb">
-    Apply task-level guardrails with retries, validation functions, and safe fallbacks.
-  </Card>
-
-  <Card title="Gemini Search & Grounding" icon="magnifying-glass" href="https://github.com/crewAIInc/crewAI-quickstarts/blob/main/Custom%20LLM/gemini_search_grounding_crewai.ipynb">
-    Connect CrewAI to Gemini with search grounding for factual, citation-rich outputs.
-  </Card>
-
-  <Card title="Gemini Video Summaries" icon="video" href="https://github.com/crewAIInc/crewAI-quickstarts/blob/main/Custom%20LLM/summarize_video_gemini_crewai.ipynb">
-    Generate video recaps using Gemini multimodal LLM and CrewAI orchestration.
-  </Card>
-</CardGroup>
-
 <CardGroup cols={2}>
-  <Card title="Browse Quickstarts" icon="bolt" href="https://github.com/crewAIInc/crewAI-quickstarts">
-    View all notebooks and feature demos showcasing specific CrewAI capabilities.
+  <Card title="Task Guardrails" icon="shield-check" href="https://github.com/crewAIInc/crewAI-quickstarts/tree/main/Task%20Guardrails"> 
+    Interactive notebooks for hands-on exploration.
   </Card>
-  <Card title="Request a cookbook" icon="message-plus" href="https://community.crewai.com">
-    Missing a pattern? Drop a request in the community forum and we’ll expand the library.
+  <Card title="Browse Quickstarts" icon="bolt" href="https://github.com/crewAIInc/crewAI-quickstarts">
+    Feature demos and small projects showcasing specific CrewAI capabilities.
   </Card>
 </CardGroup>
 
 <Tip>
 Use Cookbooks to learn a pattern quickly, then jump to Full Examples for production‑grade implementations.
 </Tip>
+
+

docs/en/index.mdx

@@ -1,105 +0,0 @@
----
-title: "CrewAI Documentation"
-description: "Build collaborative AI agents, crews, and flows — production ready from day one."
-icon: "house"
-mode: "wide"
----
-
-<div
-  style={{
-    display: 'flex',
-    flexDirection: 'column',
-    alignItems: 'center',
-    gap: 20,
-    textAlign: 'center',
-    padding: '48px 24px',
-    borderRadius: 16,
-    background: 'linear-gradient(180deg, rgba(235,102,88,0.12) 0%, rgba(201,76,60,0.08) 100%)',
-    border: '1px solid rgba(235,102,88,0.18)'
-  }}
->
-  <img src="/images/crew_only_logo.png" alt="CrewAI" width="250" height="100" />
-  <div style={{ maxWidth: 720 }}>
-    <h1 style={{ marginBottom: 12 }}>Ship multi‑agent systems with confidence</h1>
-    <p style={{ color: 'var(--mint-text-2)' }}>
-      Design agents, orchestrate crews, and automate flows with guardrails, memory, knowledge, and observability baked in.
-    </p>
-  </div>
-
-  <div style={{ display: 'flex', flexWrap: 'wrap', gap: 12, justifyContent: 'center' }}>
-    <a className="button button-primary" href="/en/quickstart">Get started</a>
-    <a className="button" href="/en/changelog">View changelog</a>
-    <a className="button" href="/en/api-reference/introduction">API Reference</a>
-  </div>
-
-</div>
-
-<div style={{ marginTop: 32 }} />
-
-## Get started
-
-<CardGroup cols={3}>
-  <Card title="Introduction" href="/en/introduction" icon="sparkles">
-    Overview of CrewAI concepts, architecture, and what you can build with agents, crews, and flows.
-  </Card>
-  <Card title="Installation" href="/en/installation" icon="wrench">
-    Install via `uv`, configure API keys, and set up the CLI for local development.
-  </Card>
-  <Card title="Quickstart" href="/en/quickstart" icon="rocket">
-    Spin up your first crew in minutes. Learn the core runtime, project layout, and dev loop.
-  </Card>
-</CardGroup>
-
-## Build the basics
-
-<CardGroup cols={3}>
-  <Card title="Agents" href="/en/concepts/agents" icon="users">
-    Compose agents with tools, memory, knowledge, and structured outputs using Pydantic. Includes templates and best practices.
-  </Card>
-  <Card title="Flows" href="/en/concepts/flows" icon="arrow-progress">
-    Orchestrate start/listen/router steps, manage state, persist execution, and resume long-running workflows.
-  </Card>
-  <Card title="Tasks & Processes" href="/en/concepts/tasks" icon="check">
-    Define sequential, hierarchical, or hybrid processes with guardrails, callbacks, and human-in-the-loop triggers.
-  </Card>
-</CardGroup>
-
-## Enterprise journey
-
-<CardGroup cols={3}>
-  <Card title="Deploy automations" href="/en/enterprise/features/automations" icon="server">
-    Manage environments, redeploy safely, and monitor live runs directly from the Enterprise console.
-  </Card>
-  <Card title="Triggers & Flows" href="/en/enterprise/guides/automation-triggers" icon="bolt">
-    Connect Gmail, Slack, Salesforce, and more. Pass trigger payloads into crews and flows automatically.
-  </Card>
-  <Card title="Team management" href="/en/enterprise/guides/team-management" icon="users-gear">
-    Invite teammates, configure RBAC, and control access to production automations.
-  </Card>
-</CardGroup>
-
-## What’s new
-
-<CardGroup cols={2}>
-  <Card title="Triggers overview" href="/en/enterprise/guides/automation-triggers" icon="sparkles">
-    Unified overview for Gmail, Drive, Outlook, Teams, OneDrive, HubSpot, and more — now with sample payloads and crews.
-  </Card>
-  <Card title="Integration tools" href="/en/tools/integration/overview" icon="plug">
-    Call existing CrewAI automations or Amazon Bedrock Agents directly from your crews using the updated integration toolkit.
-  </Card>
-</CardGroup>
-
-<Callout title="Explore real-world patterns" icon="github">
-  Browse the <a href="/en/examples/cookbooks">examples and cookbooks</a> for end-to-end reference implementations across agents, flows, and enterprise automations.
-</Callout>
-
-## Stay connected
-
-<CardGroup cols={2}>
-  <Card title="Star us on GitHub" href="https://github.com/crewAIInc/crewAI" icon="star">
-    If CrewAI helps you ship faster, give us a star and share your builds with the community.
-  </Card>
-  <Card title="Join the community" href="https://community.crewai.com" icon="comments">
-    Ask questions, showcase workflows, and request features alongside other builders.
-  </Card>
-</CardGroup>

docs/en/installation.mdx

@@ -9,12 +9,14 @@ mode: "wide"
 Watch this video tutorial for a step-by-step demonstration of the installation process:
 
 <iframe
-  className="w-full aspect-video rounded-xl"
+  width="100%"
+  height="400"
   src="https://www.youtube.com/embed/-kSOTtYzgEw"
   title="CrewAI Installation Guide"
-  frameBorder="0"
+  frameborder="0"
+  style={{ borderRadius: '10px' }}
   allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
-  allowFullScreen
+  allowfullscreen
 ></iframe>
 
 ## Text Tutorial
@@ -167,7 +169,7 @@ We recommend using the `YAML` template scaffolding for a structured approach to
 <Note type="info">
 For teams and organizations, CrewAI offers enterprise deployment options that eliminate setup complexity:
 
-### CrewAI AMP (SaaS)
+### CrewAI Enterprise (SaaS)
 - Zero installation required - just sign up for free at [app.crewai.com](https://app.crewai.com)
 - Automatic updates and maintenance
 - Managed infrastructure and scaling

docs/en/learn/human-in-the-loop.mdx

@@ -22,45 +22,6 @@ Human-in-the-Loop (HITL) is a powerful approach that combines artificial intelli
         <Frame>
             <img src="/images/enterprise/crew-webhook-url.png" alt="Crew Webhook URL" />
         </Frame>
-
-        Example with Bearer authentication:
-        ```bash
-        curl -X POST {BASE_URL}/kickoff \
-          -H "Authorization: Bearer YOUR_API_TOKEN" \
-          -H "Content-Type: application/json" \
-          -d '{
-            "inputs": {
-              "topic": "AI Research"
-            },
-            "humanInputWebhook": {
-              "url": "https://your-webhook.com/hitl",
-              "authentication": {
-                "strategy": "bearer",
-                "token": "your-webhook-secret-token"
-              }
-            }
-          }'
-        ```
-
-        Or with Basic authentication:
-        ```bash
-        curl -X POST {BASE_URL}/kickoff \
-          -H "Authorization: Bearer YOUR_API_TOKEN" \
-          -H "Content-Type: application/json" \
-          -d '{
-            "inputs": {
-              "topic": "AI Research"
-            },
-            "humanInputWebhook": {
-              "url": "https://your-webhook.com/hitl",
-              "authentication": {
-                "strategy": "basic",
-                "username": "your-username",
-                "password": "your-password"
-              }
-            }
-          }'
-        ```
     </Step>
 
     <Step title="Receive Webhook Notification">
@@ -115,4 +76,4 @@ HITL workflows are particularly valuable for:
 - Complex decision-making scenarios
 - Sensitive or high-stakes operations
 - Creative tasks requiring human judgment
-- Compliance and regulatory reviews
+- Compliance and regulatory reviews 

docs/en/learn/human-input-on-execution.mdx

@@ -1,18 +1,18 @@
 ---
 title: Human Input on Execution
 description: Integrating CrewAI with human input during execution in complex decision-making processes and leveraging the full capabilities of the agent's attributes and tools.
-icon: user-plus
+icon: user-check
 mode: "wide"
 ---
 
 ## Human input in agent execution
 
-Human input is critical in several agent execution scenarios, allowing agents to request additional information or clarification when necessary.
+Human input is critical in several agent execution scenarios, allowing agents to request additional information or clarification when necessary. 
 This feature is especially useful in complex decision-making processes or when agents require more details to complete a task effectively.
 
 ## Using human input with CrewAI
 
-To integrate human input into agent execution, set the `human_input` flag in the task definition. When enabled, the agent prompts the user for input before delivering its final answer.
+To integrate human input into agent execution, set the `human_input` flag in the task definition. When enabled, the agent prompts the user for input before delivering its final answer. 
 This input can provide extra context, clarify ambiguities, or validate the agent's output.
 
 ### Example:
@@ -96,4 +96,4 @@ result = crew.kickoff()
 
 print("######################")
 print(result)
-```
+```

docs/en/learn/llm-selection-guide.mdx

@@ -44,7 +44,7 @@ The most critical step in LLM selection is understanding what your task actually
 
     - **Creative Tasks** demand a different type of cognitive capability focused on generating novel, engaging, and contextually appropriate content. This includes storytelling, marketing copy creation, and creative problem-solving. The model needs to understand nuance, tone, and audience while producing content that feels authentic and engaging rather than formulaic.
   </Tab>
-
+  
   <Tab title="Output Requirements">
     - **Structured Data** tasks require precision and consistency in format adherence. When working with JSON, XML, or database formats, the model must reliably produce syntactically correct output that can be programmatically processed. These tasks often have strict validation requirements and little tolerance for format errors, making reliability more important than creativity.
 
@@ -52,7 +52,7 @@ The most critical step in LLM selection is understanding what your task actually
 
     - **Technical Content** sits between structured data and creative content, requiring both precision and clarity. Documentation, code generation, and technical analysis need to be accurate and comprehensive while remaining accessible to the intended audience. The model must understand complex technical concepts and communicate them effectively.
   </Tab>
-
+  
   <Tab title="Context Needs">
     - **Short Context** scenarios involve focused, immediate tasks where the model needs to process limited information quickly. These are often transactional interactions where speed and efficiency matter more than deep understanding. The model doesn't need to maintain extensive conversation history or process large documents.
 
@@ -74,7 +74,7 @@ Understanding model capabilities requires looking beyond marketing claims and be
 
     However, reasoning models often come with trade-offs in terms of speed and cost. They may also be less suitable for creative tasks or simple operations where their sophisticated reasoning capabilities aren't needed. Consider these models when your tasks involve genuine complexity that benefits from systematic, step-by-step analysis.
   </Accordion>
-
+  
   <Accordion title="General Purpose Models" icon="microchip">
     General purpose models offer the most balanced approach to LLM selection, providing solid performance across a wide range of tasks without extreme specialization in any particular area. These models are trained on diverse datasets and optimized for versatility rather than peak performance in specific domains.
 
@@ -82,7 +82,7 @@ Understanding model capabilities requires looking beyond marketing claims and be
 
     While general purpose models may not achieve the peak performance of specialized alternatives in specific domains, they offer operational simplicity and reduced complexity in model management. They're often the best starting point for new projects, allowing teams to understand their specific needs before potentially optimizing with more specialized models.
   </Accordion>
-
+  
   <Accordion title="Fast & Efficient Models" icon="bolt">
     Fast and efficient models prioritize speed, cost-effectiveness, and resource efficiency over sophisticated reasoning capabilities. These models are optimized for high-throughput scenarios where quick responses and low operational costs are more important than nuanced understanding or complex reasoning.
 
@@ -90,7 +90,7 @@ Understanding model capabilities requires looking beyond marketing claims and be
 
     The key consideration with efficient models is ensuring that their capabilities align with your task requirements. While they can handle many routine operations effectively, they may struggle with tasks requiring nuanced understanding, complex reasoning, or sophisticated content generation. They're best used for well-defined, routine operations where speed and cost matter more than sophistication.
   </Accordion>
-
+  
   <Accordion title="Creative Models" icon="pen">
     Creative models are specifically optimized for content generation, writing quality, and creative thinking tasks. These models typically excel at understanding nuance, tone, and style while producing engaging, contextually appropriate content that feels natural and authentic.
 
@@ -98,7 +98,7 @@ Understanding model capabilities requires looking beyond marketing claims and be
 
     When selecting creative models, consider not just their ability to generate text, but their understanding of audience, context, and purpose. The best creative models can adapt their output to match specific brand voices, target different audience segments, and maintain consistency across extended content pieces.
   </Accordion>
-
+  
   <Accordion title="Open Source Models" icon="code">
     Open source models offer unique advantages in terms of cost control, customization potential, data privacy, and deployment flexibility. These models can be run locally or on private infrastructure, providing complete control over data handling and model behavior.
 
@@ -151,7 +151,7 @@ content_writer = Agent(
 )
 
 data_processor = Agent(
-    role="Data Analysis Specialist",
+    role="Data Analysis Specialist", 
     goal="Extract and organize key data points from research sources",
     backstory="Detail-oriented analyst focused on accuracy and efficiency",
     llm=processing_llm,  # Fast, cost-effective model for routine tasks
@@ -178,7 +178,7 @@ The key to successful multi-model implementation is understanding how different
 
     Cost considerations are particularly important for manager LLMs since they're involved in every operation. The model needs to provide sufficient capability for effective coordination while remaining cost-effective for frequent use. This often means finding models that offer good reasoning capabilities without the premium pricing of the most sophisticated options.
   </Tab>
-
+  
   <Tab title="Function Calling LLM">
     Function calling LLMs handle tool usage across all agents, making them critical for crews that rely heavily on external tools and APIs. These models need to excel at understanding tool capabilities, extracting parameters accurately, and handling tool responses effectively.
 
@@ -186,7 +186,7 @@ The key to successful multi-model implementation is understanding how different
 
     Many teams find that specialized function calling models or general purpose models with strong tool support work better than creative or reasoning-focused models for this role. The key is ensuring that the model can reliably bridge the gap between natural language instructions and structured tool calls.
   </Tab>
-
+  
   <Tab title="Agent-Specific Overrides">
     Individual agents can override crew-level LLM settings when their specific needs differ significantly from the general crew requirements. This capability allows for fine-tuned optimization while maintaining operational simplicity for most agents.
 
@@ -210,7 +210,7 @@ Effective task definition is often more important than model selection in determ
 
     Common mistakes include being too vague about objectives, failing to provide necessary context, setting unclear success criteria, or combining multiple unrelated tasks into a single description. The goal is to provide enough information for the agent to succeed while maintaining focus on a single, clear objective.
   </Accordion>
-
+  
   <Accordion title="Expected Output Guidelines" icon="bullseye">
     Expected output guidelines serve as a contract between the task definition and the agent, clearly specifying what the deliverable should look like and how it will be evaluated. These guidelines should describe both the format and structure needed, as well as the key elements that must be included for the output to be considered complete.
 
@@ -230,7 +230,7 @@ Effective task definition is often more important than model selection in determ
 
     Sequential dependencies work best when there's a clear logical progression from one task to another and when the output of one task genuinely improves the quality or feasibility of subsequent tasks. However, they can create bottlenecks if not managed carefully, so it's important to identify which dependencies are truly necessary versus those that are merely convenient.
   </Tab>
-
+  
   <Tab title="Parallel Execution">
     Parallel execution becomes valuable when tasks are independent of each other, time efficiency is important, or different expertise areas are involved that don't require coordination. This approach can significantly reduce overall execution time while allowing specialized agents to work on their areas of strength simultaneously.
 
@@ -286,10 +286,10 @@ domain_expert = Agent(
     role="B2B SaaS Marketing Strategist",
     goal="Develop comprehensive go-to-market strategies for enterprise software",
     backstory="""
-    You have 10+ years of experience scaling B2B SaaS companies from Series A to IPO.
-    You understand the nuances of enterprise sales cycles, the importance of product-market
-    fit in different verticals, and how to balance growth metrics with unit economics.
-    You've worked with companies like Salesforce, HubSpot, and emerging unicorns, giving
+    You have 10+ years of experience scaling B2B SaaS companies from Series A to IPO. 
+    You understand the nuances of enterprise sales cycles, the importance of product-market 
+    fit in different verticals, and how to balance growth metrics with unit economics. 
+    You've worked with companies like Salesforce, HubSpot, and emerging unicorns, giving 
     you perspective on both established and disruptive go-to-market strategies.
     """,
     llm=LLM(model="claude-3-5-sonnet", temperature=0.3)  # Balanced creativity with domain knowledge
@@ -317,9 +317,9 @@ tech_writer = Agent(
     role="API Documentation Specialist",  # Specific role for clear LLM requirements
     goal="Create comprehensive, developer-friendly API documentation",
     backstory="""
-    You're a technical writer with 8+ years documenting REST APIs, GraphQL endpoints,
-    and SDK integration guides. You've worked with developer tools companies and
-    understand what developers need: clear examples, comprehensive error handling,
+    You're a technical writer with 8+ years documenting REST APIs, GraphQL endpoints, 
+    and SDK integration guides. You've worked with developer tools companies and 
+    understand what developers need: clear examples, comprehensive error handling, 
     and practical use cases. You prioritize accuracy and usability over marketing fluff.
     """,
     llm=LLM(
@@ -327,13 +327,13 @@ tech_writer = Agent(
         temperature=0.1  # Low temperature for accuracy
     ),
     tools=[code_analyzer_tool, api_scanner_tool],
-    verbose=True
+    verbose=True 
 )
 ```
 
 **Alignment Checklist:**
 - ✅ **Role Specificity**: Clear domain and responsibilities
-- ✅ **LLM Match**: Model strengths align with role requirements
+- ✅ **LLM Match**: Model strengths align with role requirements 
 - ✅ **Backstory Depth**: Provides domain context the LLM can leverage
 - ✅ **Tool Integration**: Tools support the agent's specialized function
 - ✅ **Parameter Tuning**: Temperature and settings optimize for role needs
@@ -351,26 +351,26 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     - Which agents handle the most complex reasoning tasks?
     - Which agents primarily do data processing or formatting?
     - Are any agents heavily tool-dependent?
-
+    
     **Action**: Document current agent roles and identify optimization opportunities.
   </Step>
-
+  
   <Step title="Implement Crew-Level Strategy" icon="users-gear">
     **Set Your Baseline:**
     ```python
     # Start with a reliable default for the crew
     default_crew_llm = LLM(model="gpt-4o-mini")  # Cost-effective baseline
-
+    
     crew = Crew(
         agents=[...],
         tasks=[...],
         memory=True
     )
     ```
-
+    
     **Action**: Establish your crew's default LLM before optimizing individual agents.
   </Step>
-
+  
   <Step title="Optimize High-Impact Agents" icon="star">
     **Identify and Upgrade Key Agents:**
     ```python
@@ -380,25 +380,25 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
         llm=LLM(model="gemini-2.5-flash-preview-05-20"),  # Premium for coordination
         # ... rest of config
     )
-
-    # Creative or customer-facing agents
+    
+    # Creative or customer-facing agents  
     content_agent = Agent(
         role="Content Creator",
         llm=LLM(model="claude-3-5-sonnet"),  # Best for writing
         # ... rest of config
     )
     ```
-
+    
     **Action**: Upgrade 20% of your agents that handle 80% of the complexity.
   </Step>
-
+  
   <Step title="Validate with Enterprise Testing" icon="test-tube">
     **Once you deploy your agents to production:**
-    - Use [CrewAI AMP platform](https://app.crewai.com) to A/B test your model selections
+    - Use [CrewAI Enterprise platform](https://app.crewai.com) to A/B test your model selections
     - Run multiple iterations with real inputs to measure consistency and performance
     - Compare cost vs. performance across your optimized setup
     - Share results with your team for collaborative decision-making
-
+    
     **Action**: Replace guesswork with data-driven validation using the testing platform.
   </Step>
 </Steps>
@@ -413,7 +413,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
 
     However, reasoning models often come with higher costs and slower response times, so they're best reserved for tasks where their sophisticated capabilities provide genuine value rather than being used for simple operations that don't require complex reasoning.
   </Tab>
-
+  
   <Tab title="Creative Models">
     Creative models become valuable when content generation is the primary output and the quality, style, and engagement level of that content directly impact success. These models excel when writing quality and style matter significantly, creative ideation or brainstorming is needed, or brand voice and tone are important considerations.
 
@@ -421,7 +421,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
 
     Creative models may be less suitable for technical or analytical tasks where precision and factual accuracy are more important than engagement and style. They're best used when the creative and communicative aspects of the output are primary success factors.
   </Tab>
-
+  
   <Tab title="Efficient Models">
     Efficient models are ideal for high-frequency, routine operations where speed and cost optimization are priorities. These models work best when tasks have clear, well-defined parameters and don't require sophisticated reasoning or creative capabilities.
 
@@ -429,7 +429,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
 
     The key with efficient models is ensuring that their capabilities align with task requirements. They can handle many routine operations effectively but may struggle with tasks requiring nuanced understanding, complex reasoning, or sophisticated content generation.
   </Tab>
-
+  
   <Tab title="Open Source Models">
     Open source models become attractive when budget constraints are significant, data privacy requirements exist, customization needs are important, or local deployment is required for operational or compliance reasons.
 
@@ -451,12 +451,12 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     ```python
     # Strategic agent gets premium model
     manager = Agent(role="Strategy Manager", llm=LLM(model="gpt-4o"))
-
-    # Processing agent gets efficient model
+    
+    # Processing agent gets efficient model  
     processor = Agent(role="Data Processor", llm=LLM(model="gpt-4o-mini"))
     ```
   </Accordion>
-
+  
   <Accordion title="Ignoring Crew-Level vs Agent-Level LLM Hierarchy" icon="shuffle">
     **The Problem**: Not understanding how CrewAI's LLM hierarchy works - crew LLM, manager LLM, and agent LLM settings can conflict or be poorly coordinated.
 
@@ -470,12 +470,12 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
         manager_llm=LLM(model="gpt-4o"),  # For crew coordination
         process=Process.hierarchical  # When using manager_llm
     )
-
+    
     # Agents inherit crew LLM unless specifically overridden
     agent1 = Agent(llm=LLM(model="claude-3-5-sonnet"))  # Override for specific needs
     ```
   </Accordion>
-
+  
   <Accordion title="Function Calling Model Mismatch" icon="screwdriver-wrench">
     **The Problem**: Choosing models based on general capabilities while ignoring function calling performance for tool-heavy CrewAI workflows.
 
@@ -493,7 +493,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     )
     ```
   </Accordion>
-
+  
   <Accordion title="Premature Optimization Without Testing" icon="gear">
     **The Problem**: Making complex model selection decisions based on theoretical performance without validating with actual CrewAI workflows and tasks.
 
@@ -503,7 +503,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     ```python
     # Start with this
     crew = Crew(agents=[...], tasks=[...], llm=LLM(model="gpt-4o-mini"))
-
+    
     # Test performance, then optimize specific agents as needed
     # Use Enterprise platform testing to validate improvements
     ```
@@ -541,7 +541,7 @@ Focus on understanding your requirements first, then select models that best mat
 
 ### Enterprise-Grade Model Validation
 
-For teams serious about optimizing their LLM selection, the **CrewAI AMP platform** provides sophisticated testing capabilities that go far beyond basic CLI testing. The platform enables comprehensive model evaluation that helps you make data-driven decisions about your LLM strategy.
+For teams serious about optimizing their LLM selection, the **CrewAI Enterprise platform** provides sophisticated testing capabilities that go far beyond basic CLI testing. The platform enables comprehensive model evaluation that helps you make data-driven decisions about your LLM strategy.
 
 <Frame>
   ![Enterprise Testing Interface](/images/enterprise/enterprise-testing.png)
@@ -571,23 +571,23 @@ The Enterprise platform transforms model selection from guesswork into a data-dr
   <Card title="Task-Driven Selection" icon="bullseye">
     Choose models based on what the task actually requires, not theoretical capabilities or general reputation.
   </Card>
-
+  
   <Card title="Capability Matching" icon="puzzle-piece">
     Align model strengths with agent roles and responsibilities for optimal performance.
   </Card>
-
+  
   <Card title="Strategic Consistency" icon="link">
     Maintain coherent model selection strategy across related components and workflows.
   </Card>
-
+  
   <Card title="Practical Testing" icon="flask">
     Validate choices through real-world usage rather than benchmarks alone.
   </Card>
-
+  
   <Card title="Iterative Improvement" icon="arrow-up">
     Start simple and optimize based on actual performance and needs.
   </Card>
-
+  
   <Card title="Operational Balance" icon="scale-balanced">
     Balance performance requirements with cost and complexity constraints.
   </Card>
@@ -614,7 +614,7 @@ These tables/metrics showcase selected leading models in each category and are n
 <Tabs>
   <Tab title="Reasoning & Planning">
     **Best for Manager LLMs and Complex Analysis**
-
+    
     | Model | Intelligence Score | Cost ($/M tokens) | Speed | Best Use in CrewAI |
     |:------|:------------------|:------------------|:------|:------------------|
     | **o3** | 70 | $17.50 | Fast | Manager LLM for complex multi-agent coordination |
@@ -625,10 +625,10 @@ These tables/metrics showcase selected leading models in each category and are n
 
     These models excel at multi-step reasoning and are ideal for agents that need to develop strategies, coordinate other agents, or analyze complex information.
   </Tab>
-
+  
   <Tab title="Coding & Technical">
     **Best for Development and Tool-Heavy Workflows**
-
+    
     | Model | Coding Performance | Tool Use Score | Cost ($/M tokens) | Best Use in CrewAI |
     |:------|:------------------|:---------------|:------------------|:------------------|
     | **Claude 4 Sonnet** | Excellent | 72.7% | $6.00 | Primary coding agent, technical documentation |
@@ -639,10 +639,10 @@ These tables/metrics showcase selected leading models in each category and are n
 
     These models are optimized for code generation, debugging, and technical problem-solving, making them ideal for development-focused crews.
   </Tab>
-
+  
   <Tab title="Speed & Efficiency">
     **Best for High-Throughput and Real-Time Applications**
-
+    
     | Model | Speed (tokens/s) | Latency (TTFT) | Cost ($/M tokens) | Best Use in CrewAI |
     |:------|:-----------------|:---------------|:------------------|:------------------|
     | **Llama 4 Scout** | 2,600 | 0.33s | $0.27 | High-volume processing agents |
@@ -653,10 +653,10 @@ These tables/metrics showcase selected leading models in each category and are n
 
     These models prioritize speed and efficiency, perfect for agents handling routine operations or requiring quick responses. **Pro tip**: Pairing these models with fast inference providers like Groq can achieve even better performance, especially for open-source models like Llama.
   </Tab>
-
+  
   <Tab title="Balanced Performance">
     **Best All-Around Models for General Crews**
-
+    
     | Model | Overall Score | Versatility | Cost ($/M tokens) | Best Use in CrewAI |
     |:------|:--------------|:------------|:------------------|:------------------|
     | **GPT-4.1** | 53 | Excellent | $3.50 | General-purpose crew LLM |
@@ -677,19 +677,19 @@ These tables/metrics showcase selected leading models in each category and are n
 
     **Strategy**: Implement a multi-model approach where premium models handle strategic thinking while efficient models handle routine operations.
   </Accordion>
-
+  
   <Accordion title="Cost-Conscious Crews" icon="dollar-sign">
     **When budget is a primary constraint**: Focus on models like **DeepSeek R1**, **Llama 4 Scout**, or **Gemini 2.0 Flash**. These provide strong performance at significantly lower costs.
 
     **Strategy**: Use cost-effective models for most agents, reserving premium models only for the most critical decision-making roles.
   </Accordion>
-
+  
   <Accordion title="Specialized Workflows" icon="screwdriver-wrench">
     **For specific domain expertise**: Choose models optimized for your primary use case. **Claude 4** series for coding, **Gemini 2.5 Pro** for research, **Llama 405B** for function calling.
 
     **Strategy**: Select models based on your crew's primary function, ensuring the core capability aligns with model strengths.
   </Accordion>
-
+  
   <Accordion title="Enterprise & Privacy" icon="shield">
     **For data-sensitive operations**: Consider open-source models like **Llama 4** series, **DeepSeek V3**, or **Qwen3** that can be deployed locally while maintaining competitive performance.
 
@@ -715,16 +715,16 @@ These tables/metrics showcase selected leading models in each category and are n
   <Step title="Start with Proven Models">
     Begin with well-established models like **GPT-4.1**, **Claude 3.7 Sonnet**, or **Gemini 2.0 Flash** that offer good performance across multiple dimensions and have extensive real-world validation.
   </Step>
-
+  
   <Step title="Identify Specialized Needs">
     Determine if your crew has specific requirements (coding, reasoning, speed) that would benefit from specialized models like **Claude 4 Sonnet** for development or **o3** for complex analysis. For speed-critical applications, consider fast inference providers like **Groq** alongside model selection.
   </Step>
-
+  
   <Step title="Implement Multi-Model Strategy">
     Use different models for different agents based on their roles. High-capability models for managers and complex tasks, efficient models for routine operations.
   </Step>
-
+  
   <Step title="Monitor and Optimize">
     Track performance metrics relevant to your use case and be prepared to adjust model selections as new models are released or pricing changes.
   </Step>
-</Steps>
+</Steps> 

docs/en/learn/using-annotations.mdx

@@ -42,15 +42,6 @@ class LinkedinProfileCrew():
 
 The `@CrewBase` annotation is used to decorate the main crew class. This class typically contains configurations and methods for creating agents, tasks, and the crew itself.
 
-<Tip>
-`@CrewBase` does more than register the class:
-
-- **Configuration bootstrapping:** looks for `agents_config` and `tasks_config` (defaulting to `config/agents.yaml` and `config/tasks.yaml`) beside the class file, loads them at instantiation, and safely falls back to empty dicts if files are missing.
-- **Decorator orchestration:** keeps memoized references to every method marked with `@agent`, `@task`, `@before_kickoff`, or `@after_kickoff` so they are instantiated once per crew and executed in declaration order.
-- **Hook wiring:** automatically attaches the preserved kickoff hooks to the `Crew` object returned by the `@crew` method, making them run before and after `.kickoff()`.
-- **MCP integration:** when the class defines `mcp_server_params`, `get_mcp_tools()` lazily starts an MCP server adapter, hydrates the declared tools, and an internal after-kickoff hook stops the adapter. See [MCP overview](/en/mcp/overview) for adapter configuration details.
-</Tip>
-
 ### 2. Tool Definition
 
 ```python
@@ -109,7 +100,7 @@ def crew(self) -> Crew:
         process=Process.sequential,
         verbose=True
     )
-```
+``` 
 
 The `@crew` annotation is used to decorate the method that creates and returns the `Crew` object. This method assembles all the components (agents and tasks) into a functional crew.
 
@@ -148,4 +139,4 @@ Note how the `llm` and `tools` in the YAML file correspond to the methods decora
 - **Flexibility**: Design your crew to be flexible by allowing easy addition or removal of agents and tasks.
 - **YAML-Code Correspondence**: Ensure that the names and structures in your YAML files correspond correctly to the decorated methods in your Python code.
 
-By following these guidelines and properly using annotations, you can create well-structured and maintainable crews using the CrewAI framework.
+By following these guidelines and properly using annotations, you can create well-structured and maintainable crews using the CrewAI framework. 

docs/en/mcp/overview.mdx

@@ -21,12 +21,14 @@ We currently support the following transport mechanisms:
 Watch this video tutorial for a comprehensive guide on MCP integration with CrewAI:
 
 <iframe
-  className="w-full aspect-video rounded-xl"
+  width="100%"
+  height="400"
   src="https://www.youtube.com/embed/TpQ45lAZh48"
   title="CrewAI MCP Integration Guide"
-  frameBorder="0"
+  frameborder="0"
+  style={{ borderRadius: '10px' }}
   allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
-  allowFullScreen
+  allowfullscreen
 ></iframe>
 
 ## Installation
@@ -173,16 +175,6 @@ class CrewWithMCP:
     # ... rest of your crew setup ...
 ```
 
-<Tip>
-When a crew class is decorated with `@CrewBase`, the adapter lifecycle is managed for you:
-
-- The first call to `get_mcp_tools()` lazily creates a shared `MCPServerAdapter` that is reused by every agent in the crew.
-- The adapter automatically shuts down after `.kickoff()` completes thanks to an implicit after-kickoff hook injected by `@CrewBase`, so no manual cleanup is required.
-- If `mcp_server_params` is not defined, `get_mcp_tools()` simply returns an empty list, allowing the same code paths to run with or without MCP configured.
-
-This makes it safe to call `get_mcp_tools()` from multiple agent methods or selectively enable MCP per environment.
-</Tip>
-
 ### Connection Timeout Configuration
 
 You can configure the connection timeout for MCP servers by setting the `mcp_connect_timeout` class attribute. If no timeout is specified, it defaults to 30 seconds.

docs/en/observability/braintrust.mdx

@@ -1,237 +0,0 @@
----
-title: Braintrust
-description: Braintrust integration for CrewAI with OpenTelemetry tracing and evaluation
-icon: magnifying-glass-chart
-mode: "wide"
----
-
-# Braintrust Integration
-
-This guide demonstrates how to integrate **Braintrust** with **CrewAI** using OpenTelemetry for comprehensive tracing and evaluation. By the end of this guide, you will be able to trace your CrewAI agents, monitor their performance, and evaluate their outputs using Braintrust's powerful observability platform.
-
-> **What is Braintrust?** [Braintrust](https://www.braintrust.dev) is an AI evaluation and observability platform that provides comprehensive tracing, evaluation, and monitoring for AI applications with built-in experiment tracking and performance analytics.
-
-## Get Started
-
-We'll walk through a simple example of using CrewAI and integrating it with Braintrust via OpenTelemetry for comprehensive observability and evaluation.
-
-### Step 1: Install Dependencies
-
-```bash
-uv add braintrust[otel] crewai crewai-tools opentelemetry-instrumentation-openai opentelemetry-instrumentation-crewai python-dotenv
-```
-
-### Step 2: Set Up Environment Variables
-
-Setup Braintrust API keys and configure OpenTelemetry to send traces to Braintrust. You'll need a Braintrust API key and your OpenAI API key.
-
-```python
-import os
-from getpass import getpass
-
-# Get your Braintrust credentials
-BRAINTRUST_API_KEY = getpass("🔑 Enter your Braintrust API Key: ")
-
-# Get API keys for services
-OPENAI_API_KEY = getpass("🔑 Enter your OpenAI API key: ")
-
-# Set environment variables
-os.environ["BRAINTRUST_API_KEY"] = BRAINTRUST_API_KEY
-os.environ["BRAINTRUST_PARENT"] = "project_name:crewai-demo"
-os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
-```
-
-### Step 3: Initialize OpenTelemetry with Braintrust
-
-Initialize the Braintrust OpenTelemetry instrumentation to start capturing traces and send them to Braintrust.
-
-```python
-import os
-from typing import Any, Dict
-
-from braintrust.otel import BraintrustSpanProcessor
-from crewai import Agent, Crew, Task
-from crewai.llm import LLM
-from opentelemetry import trace
-from opentelemetry.instrumentation.crewai import CrewAIInstrumentor
-from opentelemetry.instrumentation.openai import OpenAIInstrumentor
-from opentelemetry.sdk.trace import TracerProvider
-
-def setup_tracing() -> None:
-    """Setup OpenTelemetry tracing with Braintrust."""
-    current_provider = trace.get_tracer_provider()
-    if isinstance(current_provider, TracerProvider):
-        provider = current_provider
-    else:
-        provider = TracerProvider()
-        trace.set_tracer_provider(provider)
-
-    provider.add_span_processor(BraintrustSpanProcessor())
-    CrewAIInstrumentor().instrument(tracer_provider=provider)
-    OpenAIInstrumentor().instrument(tracer_provider=provider)
-
-
-setup_tracing()
-```
-
-### Step 4: Create a CrewAI Application
-
-We'll create a CrewAI application where two agents collaborate to research and write a blog post about AI advancements, with comprehensive tracing enabled.
-
-```python
-from crewai import Agent, Crew, Process, Task
-from crewai_tools import SerperDevTool
-
-def create_crew() -> Crew:
-    """Create a crew with multiple agents for comprehensive tracing."""
-    llm = LLM(model="gpt-4o-mini")
-    search_tool = SerperDevTool()
-
-    # Define agents with specific roles
-    researcher = Agent(
-        role="Senior Research Analyst",
-        goal="Uncover cutting-edge developments in AI and data science",
-        backstory="""You work at a leading tech think tank.
-        Your expertise lies in identifying emerging trends.
-        You have a knack for dissecting complex data and presenting actionable insights.""",
-        verbose=True,
-        allow_delegation=False,
-        llm=llm,
-        tools=[search_tool],
-    )
-
-    writer = Agent(
-        role="Tech Content Strategist",
-        goal="Craft compelling content on tech advancements",
-        backstory="""You are a renowned Content Strategist, known for your insightful and engaging articles.
-        You transform complex concepts into compelling narratives.""",
-        verbose=True,
-        allow_delegation=True,
-        llm=llm,
-    )
-
-    # Create tasks for your agents
-    research_task = Task(
-        description="""Conduct a comprehensive analysis of the latest advancements in {topic}.
-        Identify key trends, breakthrough technologies, and potential industry impacts.""",
-        expected_output="Full analysis report in bullet points",
-        agent=researcher,
-    )
-
-    writing_task = Task(
-        description="""Using the insights provided, develop an engaging blog
-        post that highlights the most significant {topic} advancements.
-        Your post should be informative yet accessible, catering to a tech-savvy audience.
-        Make it sound cool, avoid complex words so it doesn't sound like AI.""",
-        expected_output="Full blog post of at least 4 paragraphs",
-        agent=writer,
-        context=[research_task],
-    )
-
-    # Instantiate your crew with a sequential process
-    crew = Crew(
-        agents=[researcher, writer], 
-        tasks=[research_task, writing_task], 
-        verbose=True, 
-        process=Process.sequential
-    )
-
-    return crew
-
-def run_crew():
-    """Run the crew and return results."""
-    crew = create_crew()
-    result = crew.kickoff(inputs={"topic": "AI developments"})
-    return result
-
-# Run your crew
-if __name__ == "__main__":
-    # Instrumentation is already initialized above in this module
-    result = run_crew()
-    print(result)
-```
-
-### Step 5: View Traces in Braintrust
-
-After running your crew, you can view comprehensive traces in Braintrust through different perspectives:
-
-<Tabs>
-  <Tab title="Trace">
-    <Frame>
-      <img src="/images/braintrust-trace-view.png" alt="Braintrust Trace View"/>
-    </Frame>
-  </Tab>
-  
-  <Tab title="Timeline">
-    <Frame>
-      <img src="/images/braintrust-timeline-view.png" alt="Braintrust Timeline View"/>
-    </Frame>
-  </Tab>
-  
-  <Tab title="Thread">
-    <Frame>
-      <img src="/images/braintrust-thread-view.png" alt="Braintrust Thread View"/>
-    </Frame>
-  </Tab>
-</Tabs>
-
-### Step 6: Evaluate via SDK (Experiments)
-
-You can also run evaluations using Braintrust's Eval SDK. This is useful for comparing versions or scoring outputs offline. Below is a Python example using the `Eval` class with the crew we created above:
-
-```python
-# eval_crew.py
-from braintrust import Eval
-from autoevals import Levenshtein
-
-def evaluate_crew_task(input_data):
-    """Task function that wraps our crew for evaluation."""
-    crew = create_crew()
-    result = crew.kickoff(inputs={"topic": input_data["topic"]})
-    return str(result)
-
-Eval(
-    "AI Research Crew",  # Project name
-    {
-        "data": lambda: [
-            {"topic": "artificial intelligence trends 2024"},
-            {"topic": "machine learning breakthroughs"},
-            {"topic": "AI ethics and governance"},
-        ],
-        "task": evaluate_crew_task,
-        "scores": [Levenshtein],
-    },
-)
-```
-
-Setup your API key and run:
-
-```bash
-export BRAINTRUST_API_KEY="YOUR_API_KEY"
-braintrust eval eval_crew.py
-```
-
-See the [Braintrust Eval SDK guide](https://www.braintrust.dev/docs/start/eval-sdk) for more details.
-
-### Key Features of Braintrust Integration
-
-- **Comprehensive Tracing**: Track all agent interactions, tool usage, and LLM calls
-- **Performance Monitoring**: Monitor execution times, token usage, and success rates
-- **Experiment Tracking**: Compare different crew configurations and models
-- **Automated Evaluation**: Set up custom evaluation metrics for crew outputs
-- **Error Tracking**: Monitor and debug failures across your crew executions
-- **Cost Analysis**: Track token usage and associated costs
-
-### Version Compatibility Information
-- Python 3.8+
-- CrewAI >= 0.86.0
-- Braintrust >= 0.1.0
-- OpenTelemetry SDK >= 1.31.0
-
-### References
-- [Braintrust Documentation](https://www.braintrust.dev/docs) - Overview of the Braintrust platform
-- [Braintrust CrewAI Integration](https://www.braintrust.dev/docs/integrations/crew-ai) - Official CrewAI integration guide
-- [Braintrust Eval SDK](https://www.braintrust.dev/docs/start/eval-sdk) - Run experiments via the SDK
-- [CrewAI Documentation](https://docs.crewai.com/) - Overview of the CrewAI framework
-- [OpenTelemetry Docs](https://opentelemetry.io/docs/) - OpenTelemetry guide
-- [Braintrust GitHub](https://github.com/braintrustdata/braintrust) - Source code for Braintrust SDK

docs/en/observability/neatlogs.mdx

@@ -89,9 +89,10 @@ All with just two lines of code.
 ### 🔍 Full Demo (4 min)
 
 <iframe
-  className="w-full aspect-video rounded-xl"
+  width="100%"
+  height="315"
   src="https://www.youtube.com/embed/8KDme9T2I7Q?si=b8oHteaBwFNs_Duk"
-  title="NeatLogs overview"
+  title="YouTube video player"
   frameBorder="0"
   allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
   allowFullScreen

docs/en/observability/tracing.mdx

@@ -1,213 +0,0 @@
----
-title: CrewAI Tracing
-description: Built-in tracing for CrewAI Crews and Flows with the CrewAI AMP platform
-icon: magnifying-glass-chart
-mode: "wide"
----
-
-# CrewAI Built-in Tracing
-
-CrewAI provides built-in tracing capabilities that allow you to monitor and debug your Crews and Flows in real-time. This guide demonstrates how to enable tracing for both **Crews** and **Flows** using CrewAI's integrated observability platform.
-
-> **What is CrewAI Tracing?** CrewAI's built-in tracing provides comprehensive observability for your AI agents, including agent decisions, task execution timelines, tool usage, and LLM calls - all accessible through the [CrewAI AMP platform](https://app.crewai.com).
-
-![CrewAI Tracing Interface](/images/crewai-tracing.png)
-
-## Prerequisites
-
-Before you can use CrewAI tracing, you need:
-
-1. **CrewAI AMP Account**: Sign up for a free account at [app.crewai.com](https://app.crewai.com)
-2. **CLI Authentication**: Use the CrewAI CLI to authenticate your local environment
-
-```bash
-crewai login
-```
-
-## Setup Instructions
-
-### Step 1: Create Your CrewAI AMP Account
-
-Visit [app.crewai.com](https://app.crewai.com) and create your free account. This will give you access to the CrewAI AMP platform where you can view traces, metrics, and manage your crews.
-
-### Step 2: Install CrewAI CLI and Authenticate
-
-If you haven't already, install CrewAI with the CLI tools:
-
-```bash
-uv add crewai[tools]
-```
-
-Then authenticate your CLI with your CrewAI AMP account:
-
-```bash
-crewai login
-```
-
-This command will:
-1. Open your browser to the authentication page
-2. Prompt you to enter a device code
-3. Authenticate your local environment with your CrewAI AMP account
-4. Enable tracing capabilities for your local development
-
-### Step 3: Enable Tracing in Your Crew
-
-You can enable tracing for your Crew by setting the `tracing` parameter to `True`:
-
-```python
-from crewai import Agent, Crew, Process, Task
-from crewai_tools import SerperDevTool
-
-# Define your agents
-researcher = Agent(
-    role="Senior Research Analyst",
-    goal="Uncover cutting-edge developments in AI and data science",
-    backstory="""You work at a leading tech think tank.
-    Your expertise lies in identifying emerging trends.
-    You have a knack for dissecting complex data and presenting actionable insights.""",
-    verbose=True,
-    tools=[SerperDevTool()],
-)
-
-writer = Agent(
-    role="Tech Content Strategist",
-    goal="Craft compelling content on tech advancements",
-    backstory="""You are a renowned Content Strategist, known for your insightful and engaging articles.
-    You transform complex concepts into compelling narratives.""",
-    verbose=True,
-)
-
-# Create tasks for your agents
-research_task = Task(
-    description="""Conduct a comprehensive analysis of the latest advancements in AI in 2024.
-    Identify key trends, breakthrough technologies, and potential industry impacts.""",
-    expected_output="Full analysis report in bullet points",
-    agent=researcher,
-)
-
-writing_task = Task(
-    description="""Using the insights provided, develop an engaging blog
-    post that highlights the most significant AI advancements.
-    Your post should be informative yet accessible, catering to a tech-savvy audience.""",
-    expected_output="Full blog post of at least 4 paragraphs",
-    agent=writer,
-)
-
-# Enable tracing in your crew
-crew = Crew(
-    agents=[researcher, writer],
-    tasks=[research_task, writing_task],
-    process=Process.sequential,
-    tracing=True,  # Enable built-in tracing
-    verbose=True
-)
-
-# Execute your crew
-result = crew.kickoff()
-```
-
-### Step 4: Enable Tracing in Your Flow
-
-Similarly, you can enable tracing for CrewAI Flows:
-
-```python
-from crewai.flow.flow import Flow, listen, start
-from pydantic import BaseModel
-
-class ExampleState(BaseModel):
-    counter: int = 0
-    message: str = ""
-
-class ExampleFlow(Flow[ExampleState]):
-    def __init__(self):
-        super().__init__(tracing=True)  # Enable tracing for the flow
-
-    @start()
-    def first_method(self):
-        print("Starting the flow")
-        self.state.counter = 1
-        self.state.message = "Flow started"
-        return "continue"
-
-    @listen("continue")
-    def second_method(self):
-        print("Continuing the flow")
-        self.state.counter += 1
-        self.state.message = "Flow continued"
-        return "finish"
-
-    @listen("finish")
-    def final_method(self):
-        print("Finishing the flow")
-        self.state.counter += 1
-        self.state.message = "Flow completed"
-
-# Create and run the flow with tracing enabled
-flow = ExampleFlow(tracing=True)
-result = flow.kickoff()
-```
-
-### Step 5: View Traces in the CrewAI AMP Dashboard
-
-After running the crew or flow, you can view the traces generated by your CrewAI application in the CrewAI AMP dashboard. You should see detailed steps of the agent interactions, tool usages, and LLM calls.
-Just click on the link below to view the traces or head over to the traces tab in the dashboard [here](https://app.crewai.com/crewai_plus/trace_batches)
-![CrewAI Tracing Interface](/images/view-traces.png)
-
-
-### Alternative: Environment Variable Configuration
-
-You can also enable tracing globally by setting an environment variable:
-
-```bash
-export CREWAI_TRACING_ENABLED=true
-```
-
-Or add it to your `.env` file:
-
-```env
-CREWAI_TRACING_ENABLED=true
-```
-
-When this environment variable is set, all Crews and Flows will automatically have tracing enabled, even without explicitly setting `tracing=True`.
-
-## Viewing Your Traces
-
-### Access the CrewAI AMP Dashboard
-
-1. Visit [app.crewai.com](https://app.crewai.com) and log in to your account
-2. Navigate to your project dashboard
-3. Click on the **Traces** tab to view execution details
-
-### What You'll See in Traces
-
-CrewAI tracing provides comprehensive visibility into:
-
-- **Agent Decisions**: See how agents reason through tasks and make decisions
-- **Task Execution Timeline**: Visual representation of task sequences and dependencies
-- **Tool Usage**: Monitor which tools are called and their results
-- **LLM Calls**: Track all language model interactions, including prompts and responses
-- **Performance Metrics**: Execution times, token usage, and costs
-- **Error Tracking**: Detailed error information and stack traces
-
-### Trace Features
-- **Execution Timeline**: Click through different stages of execution
-- **Detailed Logs**: Access comprehensive logs for debugging
-- **Performance Analytics**: Analyze execution patterns and optimize performance
-- **Export Capabilities**: Download traces for further analysis
-
-### Authentication Issues
-
-If you encounter authentication problems:
-
-1. Ensure you're logged in: `crewai login`
-2. Check your internet connection
-3. Verify your account at [app.crewai.com](https://app.crewai.com)
-
-### Traces Not Appearing
-
-If traces aren't showing up in the dashboard:
-
-1. Confirm `tracing=True` is set in your Crew/Flow
-2. Check that `CREWAI_TRACING_ENABLED=true` if using environment variables
-3. Ensure you're authenticated with `crewai login`
-4. Verify your crew/flow is actually executing

docs/en/quickstart.mdx

@@ -209,9 +209,9 @@ Follow the steps below to get Crewing! 🚣‍♂️
   </Step>
 
   <Step title="Enterprise Alternative: Create in Crew Studio">
-  For CrewAI AMP users, you can create the same crew without writing code:
+  For CrewAI Enterprise users, you can create the same crew without writing code:
 
-  1. Log in to your CrewAI AMP account (create a free account at [app.crewai.com](https://app.crewai.com))
+  1. Log in to your CrewAI Enterprise account (create a free account at [app.crewai.com](https://app.crewai.com))
   2. Open Crew Studio
   3. Type what is the automation you're trying to build
   4. Create your tasks visually and connect them in sequence
@@ -219,8 +219,8 @@ Follow the steps below to get Crewing! 🚣‍♂️
 
   ![Crew Studio Quickstart](/images/enterprise/crew-studio-interface.png)
 
-  <Card title="Try CrewAI AMP" icon="rocket" href="https://app.crewai.com">
-    Start your free account at CrewAI AMP
+  <Card title="Try CrewAI Enterprise" icon="rocket" href="https://app.crewai.com">
+    Start your free account at CrewAI Enterprise
   </Card>
   </Step>
   <Step title="View your final report">
@@ -340,17 +340,19 @@ email_summarizer_task:
 
 ## Deploying Your Crew
 
-The easiest way to deploy your crew to production is through [CrewAI AMP](http://app.crewai.com).
+The easiest way to deploy your crew to production is through [CrewAI Enterprise](http://app.crewai.com).
 
-Watch this video tutorial for a step-by-step demonstration of deploying your crew to [CrewAI AMP](http://app.crewai.com) using the CLI.
+Watch this video tutorial for a step-by-step demonstration of deploying your crew to [CrewAI Enterprise](http://app.crewai.com) using the CLI.
 
 <iframe
-  className="w-full aspect-video rounded-xl"
+  width="100%"
+  height="400"
   src="https://www.youtube.com/embed/3EqSV-CYDZA"
   title="CrewAI Deployment Guide"
-  frameBorder="0"
+  frameborder="0"
+  style={{ borderRadius: '10px' }}
   allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
-  allowFullScreen
+  allowfullscreen
 ></iframe>
 
 <CardGroup cols={2}>
@@ -359,7 +361,7 @@ Watch this video tutorial for a step-by-step demonstration of deploying your cre
     icon="rocket"
     href="http://app.crewai.com"
   >
-    Get started with CrewAI AMP and deploy your crew in a production environment with just a few clicks.
+    Get started with CrewAI Enterprise and deploy your crew in a production environment with just a few clicks.
   </Card>
   <Card
     title="Join the Community"

docs/en/tools/integration/overview.mdx

@@ -1,72 +0,0 @@
----
-title: "Overview"
-description: "Connect CrewAI agents with external automations and managed AI services"
-icon: "face-smile"
-mode: "wide"
----
-
-Integration tools let your agents hand off work to other automation platforms and managed AI services. Use them when a workflow needs to invoke an existing CrewAI deployment or delegate specialised tasks to providers such as Amazon Bedrock.
-
-## **Available Tools**
-
-<CardGroup cols={2}>
-  <Card title="CrewAI Run Automation Tool" icon="robot" href="/en/tools/integration/crewaiautomationtool">
-    Invoke live CrewAI Platform automations, pass custom inputs, and poll for results directly from your agent.
-  </Card>
-
-  <Card title="Bedrock Invoke Agent Tool" icon="aws" href="/en/tools/integration/bedrockinvokeagenttool">
-    Call Amazon Bedrock Agents from your crews, reuse AWS guardrails, and stream responses back into the workflow.
-  </Card>
-</CardGroup>
-
-## **Common Use Cases**
-
-- **Chain automations**: Kick off an existing CrewAI deployment from within another crew or flow
-- **Enterprise hand-off**: Route tasks to Bedrock Agents that already encapsulate company logic and guardrails
-- **Hybrid workflows**: Combine CrewAI reasoning with downstream systems that expose their own agent APIs
-- **Long-running jobs**: Poll external automations and merge the final results back into the current run
-
-## **Quick Start Example**
-
-```python
-from crewai import Agent, Task, Crew
-from crewai_tools import InvokeCrewAIAutomationTool
-from crewai_tools.aws.bedrock.agents.invoke_agent_tool import BedrockInvokeAgentTool
-
-# External automation
-analysis_automation = InvokeCrewAIAutomationTool(
-    crew_api_url="https://analysis-crew.acme.crewai.com",
-    crew_bearer_token="YOUR_BEARER_TOKEN",
-    crew_name="Analysis Automation",
-    crew_description="Runs the production-grade analysis pipeline",
-)
-
-# Managed agent on Bedrock
-knowledge_router = BedrockInvokeAgentTool(
-    agent_id="bedrock-agent-id",
-    agent_alias_id="prod",
-)
-
-automation_strategist = Agent(
-    role="Automation Strategist",
-    goal="Orchestrate external automations and summarise their output",
-    backstory="You coordinate enterprise workflows and know when to delegate tasks to specialised services.",
-    tools=[analysis_automation, knowledge_router],
-    verbose=True,
-)
-
-execute_playbook = Task(
-    description="Run the analysis automation and ask the Bedrock agent for executive talking points.",
-    agent=automation_strategist,
-)
-
-Crew(agents=[automation_strategist], tasks=[execute_playbook]).kickoff()
-```
-
-## **Best Practices**
-
-- **Secure credentials**: Store API keys and bearer tokens in environment variables or a secrets manager
-- **Plan for latency**: External automations may take longer—set appropriate polling intervals and timeouts
-- **Reuse sessions**: Bedrock Agents support session IDs so you can maintain context across multiple tool calls
-- **Validate responses**: Normalise remote output (JSON, text, status codes) before forwarding it to downstream tasks
-- **Monitor usage**: Track audit logs in CrewAI Platform or AWS CloudWatch to stay ahead of quota limits and failures

docs/enterprise-api.base.yaml

@@ -1,40 +1,40 @@
 openapi: 3.0.3
 info:
-  title: CrewAI AMP API
+  title: CrewAI Enterprise API
   description: |
-    REST API for interacting with your deployed CrewAI crews on CrewAI AMP.
-
+    REST API for interacting with your deployed CrewAI crews on CrewAI Enterprise.
+    
     ## Getting Started
-
-    1. **Find your crew URL**: Get your unique crew URL from the CrewAI AMP dashboard
+    
+    1. **Find your crew URL**: Get your unique crew URL from the CrewAI Enterprise dashboard
     2. **Copy examples**: Use the code examples from each endpoint page as templates
     3. **Replace placeholders**: Update URLs and tokens with your actual values
     4. **Test with your tools**: Use cURL, Postman, or your preferred API client
-
+    
     ## Authentication
-
+    
     All API requests require a bearer token for authentication. There are two types of tokens:
-
+    
     - **Bearer Token**: Organization-level token for full crew operations
     - **User Bearer Token**: User-scoped token for individual access with limited permissions
-
-    You can find your bearer tokens in the Status tab of your crew's detail page in the CrewAI AMP dashboard.
-
+    
+    You can find your bearer tokens in the Status tab of your crew's detail page in the CrewAI Enterprise dashboard.
+    
     ## Reference Documentation
-
+    
     This documentation provides comprehensive examples for each endpoint:
-
+    
     - **Request formats** with all required and optional parameters
     - **Response examples** for success and error scenarios
     - **Code samples** in multiple programming languages
     - **Authentication patterns** with proper Bearer token usage
-
+    
     Copy the examples and customize them with your actual crew URL and authentication tokens.
-
+    
     ## Workflow
-
+    
     1. **Discover inputs** using `GET /inputs`
-    2. **Start execution** using `POST /kickoff`
+    2. **Start execution** using `POST /kickoff`  
     3. **Monitor progress** using `GET /status/{kickoff_id}`
   version: 1.0.0
   contact:
@@ -43,7 +43,7 @@ info:
     url: https://crewai.com
 servers:
   - url: https://your-actual-crew-name.crewai.com
-    description: Replace with your actual deployed crew URL from the CrewAI AMP dashboard
+    description: Replace with your actual deployed crew URL from the CrewAI Enterprise dashboard
   - url: https://my-travel-crew.crewai.com
     description: Example travel planning crew (replace with your URL)
   - url: https://content-creation-crew.crewai.com
@@ -58,7 +58,7 @@ paths:
       summary: Get Required Inputs
       description: |
         **📋 Reference Example Only** - *This shows the request format. To test with your actual crew, copy the cURL example and replace the URL + token with your real values.*
-
+        
         Retrieves the list of all required input parameters that your crew expects for execution.
         Use this endpoint to discover what inputs you need to provide when starting a crew execution.
       operationId: getRequiredInputs
@@ -82,7 +82,7 @@ paths:
                   value:
                     inputs: ["budget", "interests", "duration", "age"]
                 outreach_crew:
-                  summary: Outreach crew inputs
+                  summary: Outreach crew inputs  
                   value:
                     inputs: ["name", "title", "company", "industry", "our_product", "linkedin_url"]
         '401':
@@ -97,10 +97,10 @@ paths:
       summary: Start Crew Execution
       description: |
         **📋 Reference Example Only** - *This shows the request format. To test with your actual crew, copy the cURL example and replace the URL + token with your real values.*
-
-        Initiates a new crew execution with the provided inputs. Returns a kickoff ID that can be used
+        
+        Initiates a new crew execution with the provided inputs. Returns a kickoff ID that can be used 
         to track the execution progress and retrieve results.
-
+        
         Crew executions can take anywhere from seconds to minutes depending on their complexity.
         Consider using webhooks for real-time notifications or implement polling with the status endpoint.
       operationId: startCrewExecution
@@ -152,7 +152,7 @@ paths:
                   inputs:
                     budget: "1000 USD"
                     interests: "games, tech, ai, relaxing hikes, amazing food"
-                    duration: "7 days"
+                    duration: "7 days" 
                     age: "35"
                   meta:
                     requestId: "travel-req-123"
@@ -204,9 +204,9 @@ paths:
       summary: Get Execution Status
       description: |
         **📋 Reference Example Only** - *This shows the request format. To test with your actual crew, copy the cURL example and replace the URL + token with your real values.*
-
+        
         Retrieves the current status and results of a crew execution using its kickoff ID.
-
+        
         The response structure varies depending on the execution state:
         - **running**: Execution in progress with current task info
         - **completed**: Execution finished with full results
@@ -283,9 +283,9 @@ components:
       scheme: bearer
       description: |
         **📋 Reference Documentation** - *The tokens shown in examples are placeholders for reference only.*
-
-        Use your actual Bearer Token or User Bearer Token from the CrewAI AMP dashboard for real API calls.
-
+        
+        Use your actual Bearer Token or User Bearer Token from the CrewAI Enterprise dashboard for real API calls.
+        
         **Bearer Token**: Organization-level access for full crew operations
         **User Bearer Token**: User-scoped access with limited permissions
 
@@ -309,7 +309,7 @@ components:
               description: Number of completed tasks
               example: 1
             total_tasks:
-              type: integer
+              type: integer  
               description: Total number of tasks in the crew
               example: 3
 
@@ -430,5 +430,5 @@ components:
           schema:
             $ref: '#/components/schemas/Error'
           example:
-            error: "Internal Server Error"
-            message: "An unexpected error occurred"
+            error: "Internal Server Error" 
+            message: "An unexpected error occurred" 

docs/enterprise-api.en.yaml

@@ -1,40 +1,40 @@
 openapi: 3.0.3
 info:
-  title: CrewAI AMP API
+  title: CrewAI Enterprise API
   description: |
-    REST API for interacting with your deployed CrewAI crews on CrewAI AMP.
-
+    REST API for interacting with your deployed CrewAI crews on CrewAI Enterprise.
+    
     ## Getting Started
-
-    1. **Find your crew URL**: Get your unique crew URL from the CrewAI AMP dashboard
+    
+    1. **Find your crew URL**: Get your unique crew URL from the CrewAI Enterprise dashboard
     2. **Copy examples**: Use the code examples from each endpoint page as templates
     3. **Replace placeholders**: Update URLs and tokens with your actual values
     4. **Test with your tools**: Use cURL, Postman, or your preferred API client
-
+    
     ## Authentication
-
+    
     All API requests require a bearer token for authentication. There are two types of tokens:
-
+    
     - **Bearer Token**: Organization-level token for full crew operations
     - **User Bearer Token**: User-scoped token for individual access with limited permissions
-
-    You can find your bearer tokens in the Status tab of your crew's detail page in the CrewAI AMP dashboard.
-
+    
+    You can find your bearer tokens in the Status tab of your crew's detail page in the CrewAI Enterprise dashboard.
+    
     ## Reference Documentation
-
+    
     This documentation provides comprehensive examples for each endpoint:
-
+    
     - **Request formats** with all required and optional parameters
     - **Response examples** for success and error scenarios
     - **Code samples** in multiple programming languages
     - **Authentication patterns** with proper Bearer token usage
-
+    
     Copy the examples and customize them with your actual crew URL and authentication tokens.
-
+    
     ## Workflow
-
+    
     1. **Discover inputs** using `GET /inputs`
-    2. **Start execution** using `POST /kickoff`
+    2. **Start execution** using `POST /kickoff`  
     3. **Monitor progress** using `GET /status/{kickoff_id}`
   version: 1.0.0
   contact:
@@ -43,7 +43,7 @@ info:
     url: https://crewai.com
 servers:
   - url: https://your-actual-crew-name.crewai.com
-    description: Replace with your actual deployed crew URL from the CrewAI AMP dashboard
+    description: Replace with your actual deployed crew URL from the CrewAI Enterprise dashboard
   - url: https://my-travel-crew.crewai.com
     description: Example travel planning crew (replace with your URL)
   - url: https://content-creation-crew.crewai.com
@@ -58,7 +58,7 @@ paths:
       summary: Get Required Inputs
       description: |
         **📋 Reference Example Only** - *This shows the request format. To test with your actual crew, copy the cURL example and replace the URL + token with your real values.*
-
+        
         Retrieves the list of all required input parameters that your crew expects for execution.
         Use this endpoint to discover what inputs you need to provide when starting a crew execution.
       operationId: getRequiredInputs
@@ -82,7 +82,7 @@ paths:
                   value:
                     inputs: ["budget", "interests", "duration", "age"]
                 outreach_crew:
-                  summary: Outreach crew inputs
+                  summary: Outreach crew inputs  
                   value:
                     inputs: ["name", "title", "company", "industry", "our_product", "linkedin_url"]
         '401':
@@ -97,10 +97,10 @@ paths:
       summary: Start Crew Execution
       description: |
         **📋 Reference Example Only** - *This shows the request format. To test with your actual crew, copy the cURL example and replace the URL + token with your real values.*
-
-        Initiates a new crew execution with the provided inputs. Returns a kickoff ID that can be used
+        
+        Initiates a new crew execution with the provided inputs. Returns a kickoff ID that can be used 
         to track the execution progress and retrieve results.
-
+        
         Crew executions can take anywhere from seconds to minutes depending on their complexity.
         Consider using webhooks for real-time notifications or implement polling with the status endpoint.
       operationId: startCrewExecution
@@ -152,7 +152,7 @@ paths:
                   inputs:
                     budget: "1000 USD"
                     interests: "games, tech, ai, relaxing hikes, amazing food"
-                    duration: "7 days"
+                    duration: "7 days" 
                     age: "35"
                   meta:
                     requestId: "travel-req-123"
@@ -204,9 +204,9 @@ paths:
       summary: Get Execution Status
       description: |
         **📋 Reference Example Only** - *This shows the request format. To test with your actual crew, copy the cURL example and replace the URL + token with your real values.*
-
+        
         Retrieves the current status and results of a crew execution using its kickoff ID.
-
+        
         The response structure varies depending on the execution state:
         - **running**: Execution in progress with current task info
         - **completed**: Execution finished with full results
@@ -283,12 +283,12 @@ components:
       scheme: bearer
       description: |
         **📋 Reference Documentation** - *The tokens shown in examples are placeholders for reference only.*
-
-        Use your actual Bearer Token or User Bearer Token from the CrewAI AMP dashboard for real API calls.
-
+        
+        Use your actual Bearer Token or User Bearer Token from the CrewAI Enterprise dashboard for real API calls.
+        
         **Bearer Token**: Organization-level access for full crew operations
         **User Bearer Token**: User-scoped access with limited permissions
-
+  
   schemas:
     ExecutionRunning:
       type: object
@@ -309,10 +309,10 @@ components:
               description: Number of completed tasks
               example: 1
             total_tasks:
-              type: integer
+              type: integer  
               description: Total number of tasks in the crew
               example: 3
-
+  
     ExecutionCompleted:
       type: object
       properties:
@@ -335,7 +335,7 @@ components:
           type: number
           description: Total execution time in seconds
           example: 108.5
-
+  
     ExecutionError:
       type: object
       properties:
@@ -351,7 +351,7 @@ components:
           type: number
           description: Time until error occurred in seconds
           example: 23.1
-
+  
     TaskResult:
       type: object
       properties:
@@ -371,7 +371,7 @@ components:
           type: number
           description: Time taken to execute this task in seconds
           example: 45.2
-
+  
     Error:
       type: object
       properties:
@@ -383,7 +383,7 @@ components:
           type: string
           description: Detailed error message
           example: "Invalid bearer token provided"
-
+  
     ValidationError:
       type: object
       properties:
@@ -401,7 +401,7 @@ components:
               items:
                 type: string
               example: ["budget", "interests"]
-
+  
   responses:
     UnauthorizedError:
       description: Authentication failed - check your bearer token
@@ -412,7 +412,7 @@ components:
           example:
             error: "Unauthorized"
             message: "Invalid or missing bearer token"
-
+  
     NotFoundError:
       description: Resource not found
       content:
@@ -422,7 +422,7 @@ components:
           example:
             error: "Not Found"
             message: "The requested resource was not found"
-
+  
     ServerError:
       description: Internal server error
       content:
@@ -430,5 +430,6 @@ components:
           schema:
             $ref: '#/components/schemas/Error'
           example:
-            error: "Internal Server Error"
+            error: "Internal Server Error" 
             message: "An unexpected error occurred"
+

docs/enterprise-api.ko.yaml

@@ -2,8 +2,8 @@ openapi: 3.0.3
 info:
   title: CrewAI 엔터프라이즈 API
   description: |
-    CrewAI AMP에 배포된 crew와 상호작용하기 위한 REST API입니다.
-
+    CrewAI Enterprise에 배포된 crew와 상호작용하기 위한 REST API입니다.
+    
     ## 시작하기
     1. **Crew URL 확인**: 대시보드에서 고유한 crew URL을 확인하세요
     2. **예제 복사**: 각 엔드포인트의 예제를 템플릿으로 사용하세요
@@ -25,7 +25,7 @@ paths:
       summary: 필요 입력값 조회
       description: |
         **📋 참조 예제만 제공** - *요청 형식을 보여줍니다. 실제 호출은 cURL 예제를 복사해 URL과 토큰을 교체하세요.*
-
+        
         실행에 필요한 입력 파라미터 목록을 반환합니다.
       operationId: getRequiredInputs
       responses:
@@ -52,7 +52,7 @@ paths:
       summary: Crew 실행 시작
       description: |
         **📋 참조 예제만 제공** - *요청 형식을 보여줍니다. 실제 호출은 cURL 예제를 복사해 URL과 토큰을 교체하세요.*
-
+        
         제공된 입력으로 새로운 실행을 시작하고 kickoff ID를 반환합니다.
       operationId: startCrewExecution
       requestBody:
@@ -89,7 +89,7 @@ paths:
       summary: 실행 상태 조회
       description: |
         **📋 참조 예제만 제공** - *요청 형식을 보여줍니다. 실제 호출은 cURL 예제를 복사해 URL과 토큰을 교체하세요.*
-
+        
         kickoff ID로 실행 상태와 결과를 조회합니다.
       operationId: getExecutionStatus
       parameters:
@@ -228,3 +228,4 @@ components:
         application/json:
           schema:
             $ref: '#/components/schemas/Error'
+

docs/enterprise-api.pt-BR.yaml

@@ -1,40 +1,40 @@
 openapi: 3.0.3
 info:
-  title: CrewAI AMP API
+  title: CrewAI Enterprise API
   description: |
-    REST API para interagir com suas crews implantadas no CrewAI AMP.
-
+    REST API para interagir com suas crews implantadas no CrewAI Enterprise.
+    
     ## Introdução
-
-    1. **Encontre a URL da sua crew**: Obtenha sua URL única no painel do CrewAI AMP
+    
+    1. **Encontre a URL da sua crew**: Obtenha sua URL única no painel do CrewAI Enterprise
     2. **Copie os exemplos**: Use os exemplos de cada endpoint como modelo
     3. **Substitua os placeholders**: Atualize URLs e tokens com seus valores reais
     4. **Teste com suas ferramentas**: Use cURL, Postman ou seu cliente preferido
-
+    
     ## Autenticação
-
+    
     Todas as requisições exigem um token bearer. Existem dois tipos:
-
+    
     - **Bearer Token**: Token em nível de organização para operações completas
     - **User Bearer Token**: Token com escopo de usuário com permissões limitadas
-
-    Você encontra os tokens na aba Status da sua crew no painel do CrewAI AMP.
-
+    
+    Você encontra os tokens na aba Status da sua crew no painel do CrewAI Enterprise.
+    
     ## Documentação de Referência
-
+    
     Este documento fornece exemplos completos para cada endpoint:
-
+    
     - **Formatos de requisição** com parâmetros obrigatórios e opcionais
     - **Exemplos de resposta** para sucesso e erro
     - **Amostras de código** em várias linguagens
     - **Padrões de autenticação** com uso correto de Bearer token
-
+    
     Copie os exemplos e personalize com sua URL e tokens reais.
-
+    
     ## Fluxo
-
+    
     1. **Descubra os inputs** usando `GET /inputs`
-    2. **Inicie a execução** usando `POST /kickoff`
+    2. **Inicie a execução** usando `POST /kickoff`  
     3. **Monitore o progresso** usando `GET /status/{kickoff_id}`
   version: 1.0.0
   contact:
@@ -43,7 +43,7 @@ info:
     url: https://crewai.com
 servers:
   - url: https://your-actual-crew-name.crewai.com
-    description: Substitua pela URL real da sua crew no painel do CrewAI AMP
+    description: Substitua pela URL real da sua crew no painel do CrewAI Enterprise
 security:
   - BearerAuth: []
 paths:
@@ -52,7 +52,7 @@ paths:
       summary: Obter Inputs Requeridos
       description: |
         **📋 Exemplo de Referência** - *Mostra o formato da requisição. Para testar com sua crew real, copie o cURL e substitua URL + token.*
-
+        
         Retorna a lista de parâmetros de entrada que sua crew espera.
       operationId: getRequiredInputs
       responses:
@@ -81,7 +81,7 @@ paths:
       summary: Iniciar Execução da Crew
       description: |
         **📋 Exemplo de Referência** - *Mostra o formato da requisição. Para testar com sua crew real, copie o cURL e substitua URL + token.*
-
+        
         Inicia uma nova execução da crew com os inputs fornecidos e retorna um kickoff ID.
       operationId: startCrewExecution
       requestBody:
@@ -102,7 +102,7 @@ paths:
                     interests: "games, tech, ai, relaxing hikes, amazing food"
                     duration: "7 days"
                     age: "35"
-
+        
       responses:
         '200':
           description: Execução iniciada com sucesso
@@ -125,7 +125,7 @@ paths:
       summary: Obter Status da Execução
       description: |
         **📋 Exemplo de Referência** - *Mostra o formato da requisição. Para testar com sua crew real, copie o cURL e substitua URL + token.*
-
+        
         Retorna o status atual e os resultados de uma execução usando o kickoff ID.
       operationId: getExecutionStatus
       parameters:
@@ -163,7 +163,7 @@ components:
       scheme: bearer
       description: |
         **📋 Referência** - *Os tokens mostrados são apenas exemplos.*
-        Use seus tokens reais do painel do CrewAI AMP.
+        Use seus tokens reais do painel do CrewAI Enterprise.
 
   schemas:
     ExecutionRunning:
@@ -180,7 +180,7 @@ components:
             completed_tasks:
               type: integer
             total_tasks:
-              type: integer
+              type: integer  
 
     ExecutionCompleted:
       type: object
@@ -265,3 +265,4 @@ components:
         application/json:
           schema:
             $ref: '#/components/schemas/Error'
+