Index page and data gallery, take 1

Author: HeidiSteen

articles/search/index.yml

@@ -1,18 +1,18 @@
 ### YamlMime:Landing
 
 title: Azure AI Search documentation # < 60 chars
-summary: Information retrieval at scale for vector and text content in traditional or generative search scenarios.
+summary: Information retrieval at scale for agentic RAG, with vector and text content in traditional or generative search scenarios.
 metadata:
   title: Azure AI Search documentation
-  description: Information retrieval at scale for vector and text content in traditional or generative search scenarios.
+  description: Information retrieval at scale for agentic RAG, with vector and text content in traditional or generative search scenarios.
   ms.service: azure-ai-search
   ms.custom:
     - ignite-2023
     - ignite-2024
   ms.topic: landing-page
   author: HeidiSteen
   ms.author: heidist
-  ms.date: 02/024/2025
+  ms.date: 05/12/2025
 # linkListType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | tutorial | video | whats-new
 
 landingContent:
@@ -25,9 +25,9 @@ landingContent:
         links:
           - text: What is Azure AI Search?
             url: search-what-is-azure-search.md
-          - text: Agentic retrieval
+          - text: Agentic RAG
             url: search-agentic-retrieval-concept.md
-          - text: Semantic reranking
+          - text: Semantic ranking
             url: semantic-search-overview.md
       - linkListType: quickstart
         links:
@@ -99,18 +99,16 @@ landingContent:
             url: tutorial-optimize-indexing-push-api.md
 
   # Card
-  - title: Develop apps
+  - title: Code
     linkLists:
-      - linkListType: tutorial
+      - linkListType: get-started
         links:
-          - text: Add search to web apps
-            url: tutorial-csharp-overview.md
-      - linkListType: how-to-guide
-        links:
-          - text: Develop in .NET
-            url: search-howto-dotnet-sdk.md
-          - text: Develop in REST
-            url: search-get-started-rest.md
+          - text: Python samples
+            url: samples-python.md
+          - text: .NET samples
+            url: samples-dotnet.md
+          - text: Vector samples
+            url: https://github.com/Azure/azure-search-vector-samples
       - linkListType: reference
         links:
           - text: Azure REST API Reference

articles/search/search-data-sources-gallery.md

@@ -9,7 +9,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 04/14/2025
+ms.date: 05/12/2025
 ---
 
 # Data sources gallery
@@ -129,6 +129,66 @@ Connect to Azure Storage through Azure Data Lake Storage Gen2 to extract content
 
 ---
 
+## Logic app connectors (preview)
+
+Pull in content [using logic app workflows](search-how-to-index-logic-apps-indexers.md) and the following supported data sources. 
+
+:::row:::
+:::column span="":::
+
+---
+
+### SharePoint
+
+By [Logic Apps](/azure/logic-apps/logic-apps-overview)
+
+Extract blob metadata and content, serialized into JSON documents, and imported into a search index as search documents. Set properties in both data source and indexer definitions to optimize for various blob content types. Change detection is supported automatically.
+
+[More details](search-how-to-index-logic-apps-indexers.md#supported-connectors)
+
+
+:::column-end:::
+:::column span="":::
+
+---
+
+### OneDrive
+
+By [Logic Apps](/azure/logic-apps/logic-apps-overview)
+
+Extract blob metadata and content, serialized into JSON documents, and imported into a search index as search documents. Set properties in both data source and indexer definitions to optimize for various blob content types. Change detection is supported automatically.
+
+[More details](search-how-to-index-logic-apps-indexers.md#supported-connectors)
+
+
+:::column-end:::
+:::column span="":::
+
+---
+
+### OneDrive for Business
+
+By [Logic Apps](/azure/logic-apps/logic-apps-overview)
+
+Extract blob metadata and content, serialized into JSON documents, and imported into a search index as search documents. Set properties in both data source and indexer definitions to optimize for various blob content types. Change detection is supported automatically.
+
+[More details](search-how-to-index-logic-apps-indexers.md#supported-connectors)
+
+:::column-end:::
+:::column span="":::
+
+---
+:::column-end:::
+:::row-end:::
+:::row:::
+:::column span="":::
+
+   :::column-end:::
+   :::column span="":::
+   :::column-end:::
+
+:::row-end:::
+
 <a name="preview"></a>
 
 ## Preview data sources by Azure AI Search