@@ -8,7 +8,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 05/28/2024
+ms.date: 01/15/2025
 ---
 
 # Add a custom skill to an Azure AI Search enrichment pipeline
@@ -23,13 +23,13 @@ If you're building a custom skill, this article describes the interface you use
 
 Building a custom skill gives you a way to insert transformations unique to your content. For example, you could build custom classification models to differentiate business and financial contracts and documents, or add a speech recognition skill to reach deeper into audio files for relevant content. For a step-by-step example, see [Example: Creating a custom skill for AI enrichment](cognitive-search-create-custom-skill-example.md).
 
-## Set the endpoint and timeout interval
+## Set the endpoint and time-out interval
 
 The interface for a custom skill is specified through the [Custom Web API skill](cognitive-search-custom-skill-web-api.md).
 
 ```json
 "@odata.type": "#Microsoft.Skills.Custom.WebApiSkill",
-"description": "This skill has a 230 second timeout",
+"description": "This skill has a 230 second time-out",
 "uri": "https://[your custom skill uri goes here]",
 "authResourceId": "[for managed identity connections, your app's client ID goes here]",
 "timeout": "PT230S",
@@ -45,7 +45,7 @@ If instead your function or app uses Azure managed identities and Azure roles fo
 
 + Your [custom skill definition](cognitive-search-custom-skill-web-api.md) must include an `authResourceId` property. This property takes an application (client) ID, in a [supported format](/azure/active-directory/develop/security-best-practices-for-app-registration#application-id-uri): `api://<appId>`.
 
-By default, the connection to the endpoint times out if a response isn't returned within a 30-second window (`PT30S`). The indexing pipeline is synchronous and indexing will produce a timeout error if a response isn't received in that time frame. You can increase the interval to a maximum value of 230 seconds by setting the timeout parameter (`PT230S`).
+By default, the connection to the endpoint times out if a response isn't returned within a 30-second window (`PT30S`). The indexing pipeline is synchronous and indexing will produce a time-out error if a response isn't received in that time frame. You can increase the interval to a maximum value of 230 seconds by setting the `timeout` parameter (`PT230S`).
 
 ## Format Web API inputs
 

@@ -6,12 +6,12 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: azure-ai-search
 ms.topic: conceptual
-ms.date: 06/06/2024
+ms.date: 01/15/2025
 ---
 
 # Skillset concepts in Azure AI Search
 
-This article is for developers who need a deeper understanding of skillset concepts and composition, and assumes familiarity with the high-level concepts of [applied AI](cognitive-search-concept-intro.md) in Azure AI Search.
+This article is for developers who need a deeper understanding of skillset composition, and assumes familiarity with the high-level concepts of [AI enrichment](cognitive-search-concept-intro.md), or applied AI, in Azure AI Search.
 
 A skillset is a reusable object in Azure AI Search that's attached to [an indexer](search-indexer-overview.md). It contains one or more skills that call built-in AI or external custom processing over documents retrieved from an external data source.
 
@@ -21,7 +21,7 @@ The following diagram illustrates the basic data flow of skillset execution.
 
 From the onset of skillset processing to its conclusion, skills read from and write to an [*enriched document*](#enrichment-tree) that exists in memory. Initially, an enriched document is just the raw content extracted from a data source (articulated as the `"/document"` root node). With each skill execution, the enriched document gains structure and substance as each skill writes its output as nodes in the graph. 
 
-After skillset execution is done, the output of an enriched document finds its way into an index through user-defined *output field mappings*. Any raw content that you want transferred intact, from source to an index, is defined through *field mappings*.
+After skillset execution is done, the output of an enriched document finds its way into an index through user-defined *output field mappings*. Any raw content that you want transferred intact, from source to an index, is defined through *field mappings*. In contrast, *output field mappings* transfer in-memory content (nodes) to the index.
 
 To configure applied AI, specify settings in a skillset and indexer.
 
@@ -191,9 +191,11 @@ The root node for all enrichments is `"/document"`. When you're working with blo
 
 ### Skill #1: Split skill
 
-When source content consists of large chunks of text, it's helpful to break it into smaller components for greater accuracy of language, sentiment, and key phrase detection. There are two grains available: pages and sentences. A page consists of approximately 5,000 characters.
+When source content consists of large chunks of text, it's helpful to break it into smaller components for [integrated vectorization](vector-search-integrated-vectorization.md), or for greater accuracy of language, sentiment, and key phrase detection. There are two grains available: pages and sentences. A page consists of approximately 5,000 characters.
 
-A text split skill is typically first in a skillset.
+An alternative to chunking with the Split skill is through the [Document Layout skill](cognitive-search-skill-document-intelligence-layout.md), but that skill is out of scope for this article.
+
+When chunking is required, the Split skill is typically first in a skillset.
 
 ```json
 "@odata.type": "#Microsoft.Skills.Text.SplitSkill",
@@ -239,7 +241,7 @@ Customer feedback reflects a range of positive and negative experiences. The sen
 
 Given the context of `/document/reviews_text/pages/*`, both sentiment analysis and key phrase skills are invoked once for each of the items in the `pages` collection. The output from the skill will be a node under the associated page element. 
 
-You should now be able to look at the rest of the skills in the skillset and visualize how the tree of enrichments continue to grow with the execution of each skill. Some skills, such as the merge skill and the shaper skill, also create new nodes but only use data from existing nodes and don't create net new enrichments.
+You should now be able to look at the rest of the skills in the skillset and visualize how the enrichment tree grows with the execution of each skill. Some skills, such as the merge skill and the shaper skill, also create new nodes but only use data from existing nodes and don't create net new enrichments.
 
 ![enrichment tree after all skills](media/cognitive-search-working-with-skillsets/enrichment-tree-final.png "Enrichment tree after  all skills")
 

@@ -10,23 +10,23 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 05/04/2024
+ms.date: 01/15/2025
 ---
 
 # Search over Azure Blob Storage content
 
 Searching across the variety of content types stored in Azure Blob Storage can be a difficult problem to solve, but [Azure AI Search](search-what-is-azure-search.md) provides deep integration at the content layer, extracting and inferring textual information, which can then be queried in a search index.
 
-In this article, review the basic workflow for extracting content and metadata from blobs and sending it to a [search index](search-what-is-an-index.md) in Azure AI Search. The resulting index can be queried using full text search. Optionally, you can send processed blob content to a [knowledge store](knowledge-store-concept-intro.md) for non-search scenarios.
+In this article, review the basic workflow for extracting content and metadata from blobs and sending it to a [search index](search-what-is-an-index.md) in Azure AI Search. The resulting index can be queried using full text search or vector search. Optionally, you can send processed blob content to a [knowledge store](knowledge-store-concept-intro.md) for non-search scenarios.
 
 > [!NOTE]
 > Already familiar with the workflow and composition? [Configure a blob indexer](search-howto-indexing-azure-blob-storage.md) is your next step.
 
-## What it means to add full text search to blob data
+## What it means to add search over blob data
 
 Azure AI Search is a standalone search service that supports indexing and query workloads over user-defined indexes that contain your private searchable content hosted in the cloud. Co-locating your searchable content with the query engine in the cloud is necessary for performance, returning results at a speed users have come to expect from search queries.
 
-Azure AI Search integrates with Azure Blob Storage at the indexing layer, importing your blob content as search documents that are indexed into *inverted indexes* and other query structures that support free-form text queries and filter expressions. Because your blob content is indexed into a search index, you can use the full range of query features in Azure AI Search to find information in your blob content.
+Azure AI Search integrates with Azure Blob Storage at the indexing layer, importing your blob content as search documents that are indexed into *inverted indexes* and other query structures that support free-form text queries, vector queries, and filter expressions. Because your blob content is indexed into a search index, you can use the full range of query features in Azure AI Search to find information in your blob content.
 
 Inputs are your blobs, in a single container, in Azure Blob Storage. Blobs can be almost any kind of text data. If your blobs contain images, you can add [AI enrichment](cognitive-search-concept-intro.md) to create and extract text and features from images.
 
@@ -58,6 +58,8 @@ By default, most blobs are indexed as a single search document in the index, inc
 
 + [Indexing JSON blobs](search-howto-index-json-blobs.md)
 + [Indexing CSV blobs](search-howto-index-csv-blobs.md)
++ [Indexing Markdown blobs](search-how-to-index-markdown-blobs.md)
++ [Indexing plain text blobs](search-howto-index-plaintext-blobs.md)
 
 A compound or embedded document (such as a ZIP archive, a Word document with embedded Outlook email containing attachments, or an .MSG file with attachments) is also indexed as a single document. For example, all images extracted from the attachments of an .MSG file will be returned in the normalized_images field. If you have images, consider adding [AI enrichment](cognitive-search-concept-intro.md) to get more search utility from that content.
 
@@ -70,7 +72,7 @@ Textual content of a document is extracted into a string field named "content".
 
 An *indexer* is a data-source-aware subservice in Azure AI Search, equipped with internal logic for sampling data, reading and retrieving data and metadata, and serializing data from native formats into JSON documents for subsequent import. 
 
-Blobs in Azure Storage are indexed using the [blob indexer](search-howto-indexing-azure-blob-storage.md). You can invoke this indexer by using the **Azure AI Search** command in Azure Storage, the **Import data** wizard, a REST API, or the .NET SDK. In code, you use this indexer by setting the type, and by providing connection information that includes an Azure Storage account along with a blob container. You can subset your blobs by creating a virtual directory, which you can then pass as a parameter, or by filtering on a file type extension.
+Blobs in Azure Storage are indexed using the [blob indexer](search-howto-indexing-azure-blob-storage.md). You can invoke this indexer by using the **Azure AI Search** command in Azure Storage, the [**Import data** wizards](search-import-data-portal.md), a REST API, or the .NET SDK. In code, you use this indexer by setting the type, and by providing connection information that includes an Azure Storage account along with a blob container. You can subset your blobs by creating a virtual directory, which you can then pass as a parameter, or by filtering on a file type extension.
 
 An indexer ["cracks a document"](search-indexer-overview.md#document-cracking), opening a blob to inspect content. After connecting to the data source, it's the first step in the pipeline. For blob data, this is where PDF, Office docs, and other content types are detected. Document cracking with text extraction is no charge. If your blobs contain image content, images are ignored unless you [add AI enrichment](cognitive-search-concept-intro.md). Standard indexing applies only to text content.
 
@@ -92,7 +94,7 @@ By running a blob indexer over a container, you can extract text and metadata fr
 
 You can control which blobs are indexed, and which are skipped, by the blob's file type or by setting properties on the blob themselves, causing the indexer to skip over them.
 
-Include specific file extensions by setting `"indexedFileNameExtensions"` to a comma-separated list of file extensions (with a leading dot). Exclude specific file extensions by setting `"excludedFileNameExtensions"` to the extensions that should be skipped. If the same extension is in both lists, it will be excluded from indexing.
+Include specific file extensions by setting `"indexedFileNameExtensions"` to a comma-separated list of file extensions (with a leading dot). Exclude specific file extensions by setting `"excludedFileNameExtensions"` to the extensions that should be skipped. If the same extension is in both lists, it's excluded from indexing.
 
 ```http
 PUT /indexers/[indexer name]?api-version=2024-07-01
@@ -110,7 +112,7 @@ PUT /indexers/[indexer name]?api-version=2024-07-01
 
 The indexer configuration parameters apply to all blobs in the container or folder. Sometimes, you want to control how *individual blobs* are indexed.
 
-Add the following metadata properties and values to blobs in Blob Storage. When the indexer encounters this property, it will skip the blob or its content in the indexing run.
+Add the following metadata properties and values to blobs in Blob Storage. When the indexer encounters this property, it skips the blob or its content in the indexing run.
 
 | Property name | Property value | Explanation |
 | ------------- | -------------- | ----------- |
@@ -122,7 +124,7 @@ Add the following metadata properties and values to blobs in Blob Storage. When
 A common scenario that makes it easy to sort through blobs of any content type is to [index both custom metadata and system properties](search-blob-metadata-properties.md) for each blob. In this way, information for all blobs is indexed regardless of document type, stored in an index in your search service. Using your new index, you can then proceed to sort, filter, and facet across all Blob storage content.
 
 > [!NOTE]
-> Blob Index tags are natively indexed by the Blob storage service and exposed for querying. If your blobs' key/value attributes require indexing and filtering capabilities, Blob Index tags should be leveraged instead of metadata.
+> Blob Index tags are natively indexed by the Blob storage service and exposed for querying. If your blobs' key/value attributes require indexing and filtering capabilities, Blob Index tags should be used instead of metadata.
 >
 > To learn more about Blob Index, see [Manage and find data on Azure Blob Storage with Blob Index](/azure/storage/blobs/storage-manage-find-blobs).
 

@@ -11,7 +11,7 @@ ms.custom:
   - references_regions
   - build-2024
 ms.topic: conceptual
-ms.date: 10/17/2024
+ms.date: 01/15/2025
 ---
 
 # Create an Azure AI Search service in the Azure portal
@@ -119,8 +119,8 @@ Generally, choose a region near you, unless the following considerations apply:
 
 Currently, the following regions offer cross-region among all three services (Azure AI Search, Azure OpenAI, Azure AI Vision multimodal). This list isn't definitive, and there might be more choices beyond the regions listed here depending on the tier. Also, region status can change quickly, so be sure to confirm region choice before installing.
 
-+ **Americas**: West US
-+ **Europe**: France Central, North Europe, Sweden Central
++ **Americas**: West US, East US
++ **Europe**: Switzerland North, Sweden Central
 
 ## Choose a tier
 
@@ -161,7 +161,7 @@ Unless you're using the Azure portal, programmatic access to your new service re
 
    :::image type="content" source="media/search-create-service-portal/set-authentication-options.png" lightbox="media/search-create-service-portal/set-authentication-options.png" alt-text="Screenshot of the Keys page with authentication options." border="true":::
 
-An endpoint and key aren't needed for portal-based tasks. the Azure portal is already linked to your Azure AI Search resource with admin rights. For a portal walkthrough, start with [Quickstart: Create an Azure AI Search index in the Azure portal](search-get-started-portal.md).
+An endpoint and key aren't needed for portal-based tasks. The Azure portal is already linked to your Azure AI Search resource with admin rights. For a portal walkthrough, start with [Quickstart: Create an Azure AI Search index in the Azure portal](search-get-started-portal.md).
 
 ## Scale your service
 
@@ -195,7 +195,7 @@ Although most customers use just one service, service redundancy might be necess
 + Globally deployed applications might require search services in each geography to minimize latency.
 
 > [!NOTE]
-> In Azure AI Search, you cannot segregate indexing and querying operations; thus, you would never create multiple services for segregated workloads. An index is always queried on the service in which it was created (you cannot create an index in one service and copy it to another).
+> In Azure AI Search, you can't segregate indexing and querying operations; thus, you would never create multiple services for segregated workloads. An index is always queried on the service in which it was created (you can't create an index in one service and copy it to another).
 
 A second service isn't required for high availability. High availability for queries is achieved when you use two or more replicas in the same service. Replica updates are sequential, which means at least one is operational when a service update is rolled out. For more information about uptime, see [Service Level Agreements](https://azure.microsoft.com/support/legal/sla/search/v1_0/).
 

@@ -7,7 +7,7 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: azure-ai-search
 ms.topic: quickstart
-ms.date: 06/14/2024
+ms.date: 01/15/2025
 ms.custom:
   - mode-ui
 ---
@@ -54,7 +54,7 @@ There are two approaches for querying in Search explorer.
 + JSON view supports parameterized queries. Filters, orderby, select, count, searchFields, and all other parameters must be set in JSON view.
 
   > [!TIP]
-  > JSON view provides intellisense for parameter name completion. Place the cursor inside the JSON view and type a space character to show a list of all query parameters, or type a single letter like "s" to show just the query parameters starting with "s". Intellisense doesn't exclude invalid parameters so use your best judgement.
+  > JSON view provides intellisense for parameter name completion. Place the cursor inside the JSON view and type a space character to show a list of all query parameters, or type a single letter like "s" to show just the query parameters starting with "s". Intellisense doesn't exclude invalid parameters so use your best judgment.
 
   Switch to **JSON view** for parameterized queries. The examples in this article assume JSON view throughout. You can paste JSON examples from this article into the text area.
 
@@ -70,7 +70,8 @@ Equivalent syntax for an empty search is `*` or `"search": "*"`.
 
    ```json
    {
-      "search": "*"
+      "search": "*",
+      "count": true
    }
    ```
 

@@ -43,22 +43,22 @@ AI service integration refers to internal connections to an Azure AI multi-servi
 | Canada Central​​ | ✅ | ✅ | ✅ |  |
 | Canada East​​ ​ |  | ✅ | |  |
 | East US​ | ✅ | ✅ | ✅ |  |
-| East US 2 ​ | ✅ | ✅ | ✅ | Basic, S1 |
-| ​Central US​​ | ✅ | ✅ | ✅ |  |
+| East US 2 ​ | ✅ | ✅ | ✅ | |
+| ​Central US​​ | ✅ | ✅ | ✅ | |
 | North Central US​ ​ | ✅ | ✅ | |  | 
-| South Central US​  | ✅ | ✅ | ✅ | All Tiers |
+| South Central US​  | ✅ | ✅ | ✅ | |
 | West US​ ​ | ✅ | ✅ | |  |
 | West US 2​ ​ | ✅ | ✅ | ✅ | |
-| West US 3​ | ✅ | ✅ |✅ | Basic, S1 |
+| West US 3​ | ✅ | ✅ |✅ | |
 | West Central US​ ​ | ✅ | ✅ | | |
 
 ### Europe
 
 | Region | AI service integration | Semantic ranker | Availability zones | Capacity constrained |
 |--|--|--|--|--|
-| North Europe​​ | ✅ | ✅ | ✅ | S2, S3, S3, S3 HD, L1, L2 |
+| North Europe​​ | ✅ | ✅ | ✅ | All tiers|
 | West Europe​​ <sup>1</sup>| ✅ | ✅ | ✅ | All Tiers |
-| France Central​​ | ✅ | ✅ | ✅ | |
+| France Central​​ | ✅ | ✅ | ✅ | Basic, S1|
 | Germany West Central​ <sup>1</sup>​| ✅ |  | ✅ | |
 | Italy North​​ |  |  | ✅ | |
 | Norway East​​ | ✅ |  | ✅ |  |

@@ -10,7 +10,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 06/28/2024
+ms.date: 01/15/2025
 ---
 
 # Security overview for Azure AI Search
@@ -53,7 +53,7 @@ Internal traffic consists of:
 
 + Service-to-service calls for tasks like authentication and authorization through Microsoft Entra ID, resource logging sent to Azure Monitor, and [private endpoint connections](service-create-private-endpoint.md) that utilize Azure Private Link.
 + Requests made to Azure AI services APIs for [built-in skills](cognitive-search-predefined-skills.md)
-+ Requests made to the machine learning models that support [semantic ranking](semantic-search-overview.md#availability-and-pricing).
++ Requests made to the various models that support [semantic ranking](semantic-search-overview.md#availability-and-pricing).
 
 ### Outbound traffic
 

@@ -10,12 +10,12 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 06/20/2024
+ms.date: 01/15/2025
 ---
 
 # Security filters for trimming results in Azure AI Search
 
-Azure AI Search doesn't provide native document-level permissions and can't vary search results from within the same index by user permissions. As a workaround, you can create a filter that trims search results based on a string containing a group or user identity.
+Azure AI Search doesn't provide native document-level permissions and can't vary search results based on user identity. As a workaround, you can create a filter that trims search results based on a string containing a group or user identity.
 
 This article describes a pattern for security filtering having the following steps:
 

@@ -8,7 +8,7 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: azure-ai-search
 ms.topic: conceptual
-ms.date: 10/25/2024
+ms.date: 01/15/2025
 
 ---
 
@@ -55,16 +55,14 @@ You can find out more about the various tiers on the [pricing page](https://azur
 
 The supported [regions list](search-region-support.md) provides the locations where Azure AI Search is offered.
 
-Currently, several regions are at capacity for specific tiers and can't be used for new search services. If you use the Azure portal to create a search service, the Azure portal excludes any region-tier combinations that aren't available.
+Currently, several regions are capacity-constrained for specific tiers and can't be used for new search services. If you use the Azure portal to create a search service, the Azure portal excludes any region-tier combinations that aren't available.
 
 | Region | Disabled tier (SKU) due to over-capacity | Suggested alternative |
 |--------|------------------------------------------|-----------------------|
-| East US 2| Basic, S1| Central US |
-| South Central US | All tiers | Central US |
+| France Central | Basic, S1| Sweden Central, Switzerland North|
+| North Europe | All tiers | Sweden Central, Switzerland North|
+| West Europe | All tiers | Sweden Central, Switzerland North|
 | US Gov Virginia | All tiers | US Gov Arizona |
-| West Europe | All tiers | Sweden Central/North Europe |
-| West US 3| Basic, S1 | Central US |
-| North Europe | S2, S3, S3 HD, L1, L2 | UK South |
 
 ## Feature availability by tier
 
@@ -109,7 +107,7 @@ This billing model is based on the concept of applying the billing rate to the n
 
 ## Tier upgrade or downgrade
 
-There is no built-in support to upgrade or downgrade tiers. If you want to switch to a different tier, the approach is:
+There's no built-in support to upgrade or downgrade tiers. If you want to switch to a different tier, the approach is:
 
 + Create a new search service at the new tier.
 

@@ -8,7 +8,7 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: azure-ai-search
 ms.topic: conceptual
-ms.date: 09/18/2024
+ms.date: 01/15/2025
 ms.custom: references_regions
 ---
 
@@ -33,10 +33,6 @@ Once you sign up, you can immediately use either of these links to access Azure
 
 + [Sign in to Azure AI Foundry](https://ai.azure.com) for a no-code approach to deploying models on Azure OpenAI and using Azure AI Search for information retrieval. **We recommend you start here first.**
 
-<!-- Although you can create a free search service that doesn't use up your credits, we recommend provisioning the **Basic** tier so that you can work with larger indexes, more indexes, and premium features like semantic ranking.
-
-The [Azure portal](https://portal.azure.com/) is the easiest approach for first-time users who want to create and use Azure resources. You can access and manage all of your subscriptions and resources from the Azure portal. For Azure AI Search, you can use the Azure portal to build components for classic search scenarios and generative search (RAG) workloads. -->
-
 ## Step two: "Day One" tasks
 
 [**How to build and consume vector indexes in Azure AI Foundry portal**](/azure/ai-studio/how-to/index-add) is a great place to start.
@@ -74,28 +70,26 @@ Generative search requires embedding and chat models. The Azure cloud provides A
 
 Application frontends are useful if you're prototyping a solution for a wider audience. You can use Azure Web apps or build an ASP.NET MVC application for this task. Otherwise, if you're working locally, you can view output in Jupyter notebooks in Visual Studio Code or another IDE. Or view results in console apps or other apps that run on localhost.
 
-<!-- ## Check regions
+## Check regions
 
 Azure AI Search has integrated operations with applied AI in the Azure cloud. Integration depends on services running within the same region. This is a requirement for data residency and for efficient operations.
 
 Verifying region availability can save you time and frustration because you need to choose a region that supports all of the services you want to use.
 
-Start here:
-
-- [Azure AI Search region list](search-region-support.md). This list identifies region support for Azure AI Search, applied AI (Azure AI multiservice), and semantic ranking. You don't need a separate region check for applied AI.
-
-  West Europe and West US 2/3 are currently at capacity for Azure AI Search and aren't accepting new search services.
-
-Continue with the following links to review which regions also provide the model provider that you want to use.
+Start here if you want to use built-in vectorization or chat models:
 
 - [Azure OpenAI region list](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability)
 - [Azure AI Vision region list](/azure/ai-services/computer-vision/overview-image-analysis?tabs=4-0#region-availability)
 - [Azure AI Foundry region list](/azure/ai-studio/reference/region-support)
 
+Continue with the following link to confirm region and tier availability for AI Search:
+
+- [Azure AI Search region list](search-region-support.md). This list identifies region support for Azure AI Search, applied AI (Azure AI multi-service), and semantic ranking. You don't need a separate region check for applied AI.
+
 > [!TIP]
-> Currently, these regions provide the most overlap and capacity: **East US**, **East US2**, and **South Central** in the Americas; **France Central** or **Switzerland North** in Europe; **Australia East** in Asia Pacific.
+> Currently, these regions provide the most overlap and capacity: **East US**, **East US2**, **Central US​​**, and **South Central** in the Americas; **UK South** or **Switzerland North** in Europe; **Australia East** in Asia Pacific.
 >
-> For Azure AI Vision and AI Search interoperability, choose one of these regions: **East US**, **France Central**, **Korea Central**, **North Europe**, **South East Asia**, or **West US**. -->
+> For Azure AI Vision and AI Search interoperability, choose one of these regions: **East US**, **West US**, **Switzerland North**, **Korea Central**, **South East Asia**, or **Australia East**.
 
 ### Create services
 
@@ -108,9 +102,9 @@ Continue with the following links to review which regions also provide the model
 
 1. [Create an Azure OpenAI resource](/azure/ai-services/openai/how-to/create-resource?pivots=web-portal) as your model provider.
 
-1. [Create an Azure AI multiservice account](/azure/ai-services/multi-service-resource?pivots=azportal) to use applied AI in your indexing workloads and Azure AI Vision multimodal APIs as an embedding model provider. You can create and transform content during indexing if applied AI can be attached. For multimodal APIs, make sure you choose a region that provides those APIs. Look for this tile in the Azure Marketplace:
+1. [Create an Azure AI multiservice account](/azure/ai-services/multi-service-resource?pivots=azportal) to use applied AI in your indexing workloads and Azure AI Vision multimodal APIs as an embedding model provider. You can create and transform content during indexing if applied AI can be attached. For multimodal APIs, make sure you choose a region that provides those APIs. Look for this tile in Azure Marketplace:
 
-   :::image type="content" source="./media/search-try-for-free/azure-ai-service-marketplace.png" alt-text="Screenshot of the Azure AI Services offering in the Azure Marketplace.":::
+   :::image type="content" source="./media/search-try-for-free/azure-ai-service-marketplace.png" alt-text="Screenshot of the Azure AI Services offering in Azure Marketplace.":::
 
 ### Try the quickstarts