@@ -9,7 +9,7 @@ ms.custom:
   - ignite-2023
   - ignite-2024
 ms.topic: how-to
-ms.date: 04/02/2025
+ms.date: 06/11/2025
 ---
 
 # Attach an Azure AI services resource to a skillset in Azure AI Search
@@ -22,7 +22,6 @@ An Azure AI services multi-service resource provides a collection of Azure AI se
 
 + [Azure AI Vision](/azure/ai-services/computer-vision/overview) for image analysis, optical character recognition (OCR), and multimodal embeddings
 + [Azure AI Language](/azure/ai-services/language-service/overview) for language detection, entity recognition, sentiment analysis, and key phrase extraction
-+ [Azure AI Speech](/azure/ai-services/speech-service/overview) for speech to text and text to speech
 + [Azure AI Translator](/azure/ai-services/translator/translator-overview) for machine text translation
 
 Exceptions to billing through the multi-service resource include [AzureOpenAIEmbedding](cognitive-search-skill-azure-openai-embedding.md) or the [AML skill](cognitive-search-aml-skill.md) billing. Azure AI Search doesn't internally host models from Azure OpenAI or the Azure AI Foundry model catalog. Usage for AML and Azure OpenAI skills and vectorizers are through [Azure OpenAI Standard pricing](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/#pricing) and [Azure Machine Learning Standard pricing](https://azure.microsoft.com/pricing/details/machine-learning/), respectively. A few other skills, such as Text Split and Text Merge, aren't billable.

@@ -108,7 +108,7 @@ In Azure Storage, a [knowledge store](knowledge-store-concept-intro.md) can assu
 
 Enrichment is available in regions that have Azure AI services. You can check the availability of enrichment on the [regions list](search-region-support.md) page. 
 
-Billing follows a Standard pricing model. The costs of using built-in skills are passed on when a multi-region Azure AI services key is specified in the skillset. There are also costs associated with image extraction, as metered by Azure AI Search. Text extraction and utility skills, however, aren't billable. For more information, see [How you're charged for Azure AI Search](search-sku-manage-costs.md#how-youre-charged-for-azure-ai-search).
+Billing follows a Standard pricing model. The costs of using built-in skills are passed on when a multi-region Azure AI services key is specified in the skillset. There are also costs associated with image extraction, as metered by Azure AI Search. Text extraction and utility skills, however, aren't billable. For more information, see [How you're charged for Azure AI Search](search-sku-manage-costs.md#how-youre-charged-for-the-base-service).
 
 ## Checklist: A typical workflow
 

@@ -11,7 +11,7 @@ ms.custom:
   - references_regions
   - build-2024
 ms.topic: how-to
-ms.date: 04/28/2025
+ms.date: 06/11/2025
 ---
 
 # Create an Azure AI Search service in the Azure portal
@@ -116,22 +116,11 @@ In most cases, choose a region near you, unless any of the following apply:
 
 1. Do you have business continuity and disaster recovery (BCDR) requirements? Create two or more search services in [regional pairs](/azure/reliability/cross-region-replication-azure#azure-paired-regions) within [availability zones](search-reliability.md#availability-zones). For example, if you're operating in North America, you might choose East US and West US, or North Central US and South Central US, for each search service.
 
-1. Do you need [AI enrichment](cognitive-search-concept-intro.md), [integrated data chunking and vectorization](vector-search-integrated-vectorization.md), or [multimodal image search](search-get-started-portal-image-search.md)? Azure AI Search, Azure OpenAI, and Azure AI services multi-service must coexist in the same region.
+1. Do you need [AI enrichment](cognitive-search-concept-intro.md), [integrated data chunking and vectorization](vector-search-integrated-vectorization.md), or [multimodal search](multimodal-search-overview.md)? For [billing purposes](cognitive-search-attach-cognitive-services.md), Azure AI Search and Azure AI services multi-service must coexist in the same region.
 
-   + Start with [Azure OpenAI regions](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability) because they have the most variability. Azure OpenAI provides embedding models and chat models for RAG and integrated vectorization.
+   + Check [Azure AI Search regions](search-region-support.md#azure-public-regions). If you're using OCR, entity recognition, or other skills backed by Azure AI, the **AI enrichment** column indicates whether Azure AI Search and Azure AI services multi-service are in the same region.
 
-   + Check [Azure AI Search regions](search-region-support.md#azure-public-regions) for a match to your Azure OpenAI region. If you're using OCR, entity recognition, or other skills backed by Azure AI, the **AI enrichment** column indicates whether Azure AI services multi-service and Azure AI Search are in the same region.
-
-   + Check [multimodal embedding regions](/azure/ai-services/computer-vision/overview-image-analysis#region-availability) for multimodal APIs and image search. This API is accessed through an Azure AI services multi-service account, but in general, it's available in fewer regions than Azure AI services multi-service.
-
-### Regions with the most overlap
-
-Currently, the following regions offer cross-regional availability for Azure AI Search, Azure OpenAI, and Azure AI Vision multimodal:
-
-+ Americas: West US, East US
-+ Europe: Switzerland North, Sweden Central
-
-This list isn't definitive, and depending on your tier, you might have more choices. Region status can also change quickly, so confirm your region choice before you create your search service.
+   + Check [Azure AI Vision regions](/azure/ai-services/computer-vision/overview-image-analysis#region-availability) for multimodal APIs that enable text and image vectorization. These APIs are powered by Azure AI Vision and accessed through an Azure AI services multi-service resource. However, they're generally available in fewer regions than the multi-service resource itself.
 
 ## Choose a tier
 

@@ -6,7 +6,7 @@ author: haileytap
 ms.author: haileytapia
 ms.service: azure-ai-search
 ms.topic: quickstart
-ms.date: 06/04/2025
+ms.date: 06/11/2025
 ms.custom:
   - references_regions
 ---
@@ -42,7 +42,7 @@ For content extraction, you can choose either default extraction via Azure AI Se
 | Default extraction | Extracts location metadata from PDF images only. Doesn't require another Azure AI resource. |
 | Enhanced extraction | Extracts location metadata from text and images for multiple document types. Requires an [Azure AI services multi-service resource](/azure/ai-services/multi-service-resource#azure-ai-multi-services-resource-for-azure-ai-search-skills) <sup>1</sup> in a [supported region](cognitive-search-skill-document-intelligence-layout.md#supported-regions). |
 
-<sup>1</sup> For billing purposes, you must [attach your multi-service resource](cognitive-search-attach-cognitive-services.md) to the skillset in your Azure AI Search service. Unless you use a [keyless connection](cognitive-search-attach-cognitive-services.md#bill-through-a-keyless-connection) to create the skillset, both resources must be in the same region.
+<sup>1</sup> For billing purposes, you must [attach your Azure AI multi-service resource](cognitive-search-attach-cognitive-services.md) to the skillset in your Azure AI Search service. Unless you use a [keyless connection](cognitive-search-attach-cognitive-services.md#bill-through-a-keyless-connection) to create the skillset, both resources must be in the same region.
 
 ### Supported embedding methods
 
@@ -57,7 +57,7 @@ For content embedding, you can choose either image verbalization (followed by te
 
 <sup>2</sup> Azure OpenAI resources (with access to embedding models) that were created in the [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs) aren't supported. You must create an Azure OpenAI resource in the Azure portal.
 
-<sup>3</sup> For billing purposes, you must [attach your multi-service resource](cognitive-search-attach-cognitive-services.md) to the skillset in your Azure AI Search service. Unless you use a [keyless connection (preview)](cognitive-search-attach-cognitive-services.md#bill-through-a-keyless-connection) to create the skillset, both resources must be in the same region.
+<sup>3</sup> For billing purposes, you must [attach your Azure AI multi-service resource](cognitive-search-attach-cognitive-services.md) to the skillset in your Azure AI Search service. Unless you use a [keyless connection (preview)](cognitive-search-attach-cognitive-services.md#bill-through-a-keyless-connection) to create the skillset, both resources must be in the same region.
 
 <sup>4</sup> `phi-4` is only available to Azure AI Foundry projects.
 
@@ -300,7 +300,7 @@ To use the skills for multimodal embeddings:
 
 1. For the kind, select your model provider: **AI Foundry Hub catalog models** or **AI Vision vectorization**.
 
-   <!-- If it's unavailable, make sure your Azure AI Search service and Azure AI multi-service account are both in a region that [supports the AI Vision multimodal APIs](/azure/ai-services/computer-vision/how-to/image-retrieval). -->
+   If Azure AI Vision is unavailable, make sure your search service and multi-service resource are both in a [region that supports the Azure AI Vision multimodal APIs](/azure/ai-services/computer-vision/how-to/image-retrieval).
 
 1. Specify your Azure subscription, resource, and embedding model deployment.
 

@@ -9,7 +9,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: quickstart
-ms.date: 06/04/2025
+ms.date: 06/11/2025
 ---
 
 # Quickstart: Vectorize text in the Azure portal
@@ -42,7 +42,7 @@ The **Import and vectorize data wizard** [supports a wide range of Azure data so
 
 ### Supported embedding models
 
-For integrated vectorization, you must use one of the following embedding models on an Azure AI platform in the [same region as Azure AI Search](search-create-service-portal.md#regions-with-the-most-overlap). Deployment instructions are provided in a [later section](#prepare-embedding-model).
+For integrated vectorization, you must use one of the following embedding models on an Azure AI platform. Deployment instructions are provided in a [later section](#prepare-embedding-model).
 
 | Provider | Supported models |
 |--|--|
@@ -54,7 +54,7 @@ For integrated vectorization, you must use one of the following embedding models
 
 <sup>2</sup> Azure OpenAI resources (with access to embedding models) that were created in the [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs) aren't supported. Only Azure OpenAI resources created in the Azure portal are compatible with the [Azure OpenAI Embedding skill](cognitive-search-skill-azure-openai-embedding.md).
 
-<sup>3</sup> For billing purposes, you must [attach your multi-service resource](cognitive-search-attach-cognitive-services.md) to the skillset in your Azure AI Search service. Unless you use a [keyless connection (preview)](cognitive-search-attach-cognitive-services.md#bill-through-a-keyless-connection) to create the skillset, both resources must be in the same region.
+<sup>3</sup> For billing purposes, you must [attach your Azure AI multi-service resource](cognitive-search-attach-cognitive-services.md) to the skillset in your Azure AI Search service. Unless you use a [keyless connection (preview)](cognitive-search-attach-cognitive-services.md#bill-through-a-keyless-connection) to create the skillset, both resources must be in the same region.
 
 <sup>4</sup> The Azure AI Vision multimodal embedding model is available in [select regions](/azure/ai-services/computer-vision/overview-image-analysis#region-availability).
 
@@ -375,7 +375,7 @@ In this step, you specify an embedding model to vectorize chunked data. Chunking
 
    + Azure AI Foundry model catalog
 
-   + An Azure AI Vision multimodal resource in the same region as Azure AI Search. If there's no [Azure AI services multi-service account](/azure/ai-services/multi-service-resource#azure-ai-multi-services-resource-for-azure-ai-search-skills) in the same region, this option isn't available.
+   + Azure AI Vision (via an [Azure AI services multi-service resource](/azure/ai-services/multi-service-resource#azure-ai-multi-services-resource-for-azure-ai-search-skills) in the same region as Azure AI Search)
 
 1. Specify the Azure subscription.
 
@@ -385,11 +385,11 @@ In this step, you specify an embedding model to vectorize chunked data. Chunking
 
    + For AI Foundry model catalog, select the model you deployed in [Prepare embedding model](#prepare-embedding-model).
 
-   + For AI Vision multimodal embeddings, select your multi-service account.
+   + For AI Vision multimodal embeddings, select your multi-service resource.
 
 1. For the authentication type, select **System assigned identity**.
 
-   + The identity should have a **Cognitive Services User** role on the Azure AI services multi-services account.
+   + The identity should have a **Cognitive Services User** role on the Azure AI services multi-service resource.
 
 1. Select the checkbox that acknowledges the billing effects of using these resources.
 

@@ -8,7 +8,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2024
 ms.topic: quickstart
-ms.date: 03/04/2025
+ms.date: 06/11/2025
 ---
 
 # Quickstart: Generative search (RAG) using grounding data from Azure AI Search
@@ -24,14 +24,11 @@ In this quickstart, you send queries to a chat completion model for a conversati
   - [Deploy the chat completion model](/azure/ai-foundry/how-to/deploy-models-openai) in Azure AI Foundry or [use another approach](/azure/ai-services/openai/how-to/working-with-models).
 
 - An [Azure AI Search resource](search-create-service-portal.md).
-  - Use the same region as your Azure OpenAI resource.
   - We recommend using the Basic tier or higher.
   - [Enable semantic ranking](semantic-how-to-enable-disable.md).
 
 - [Visual Studio Code](https://code.visualstudio.com/download) with the [Python extension](https://marketplace.visualstudio.com/items?itemName=ms-python.python) and the [Jupyter package](https://pypi.org/project/jupyter/). For more information, see [Python in Visual Studio Code](https://code.visualstudio.com/docs/languages/python).
 
-To meet the same-region requirement, start by reviewing the [regions for the chat model](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability) you want to use. After you identify a region, confirm that Azure AI Search is available in the [same region](search-region-support.md#azure-public-regions).
-
 ## Download file
 
 [Download a Jupyter notebook](https://github.com/Azure-Samples/azure-search-python-samples/tree/main/Quickstart-RAG) from GitHub to send the requests in this quickstart. For more information, see [Downloading files from GitHub](https://docs.github.com/get-started/start-your-journey/downloading-files-from-github).

@@ -7,7 +7,7 @@ author: haileytap
 ms.author: haileytapia
 ms.service: azure-ai-search
 ms.topic: how-to
-ms.date: 04/29/2025
+ms.date: 06/11/2025
 ---
 
 # Set up integrated vectorization in Azure AI Search using REST
@@ -42,7 +42,7 @@ Integrated vectorization works with [all supported data sources](search-indexer-
 
 ### Supported embedding models
 
-For integrated vectorization, you must use one of the following embedding models on an Azure AI platform in the [same region as Azure AI Search](search-create-service-portal.md#regions-with-the-most-overlap). Deployment instructions are provided in a [later section](#prepare-your-embedding-model).
+For integrated vectorization, you must use one of the following embedding models on an Azure AI platform. Deployment instructions are provided in a [later section](#prepare-your-embedding-model).
 
 | Provider | Supported models |
 |--|--|
@@ -52,7 +52,7 @@ For integrated vectorization, you must use one of the following embedding models
 
 <sup>1</sup> The endpoint of your Azure OpenAI resource must have a [custom subdomain](/azure/ai-services/cognitive-services-custom-subdomains), such as `https://my-unique-name.openai.azure.com`. If you created your resource in the [Azure portal](https://portal.azure.com/), this subdomain was automatically generated during resource setup.
 
-<sup>2</sup> Azure OpenAI resources (with access to embedding models) that were created in the [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs) aren't supported. Only Azure OpenAI resources created in the Azure portal are compatible with the [Azure OpenAI Embedding skill](cognitive-search-skill-azure-openai-embedding.md) integration.
+<sup>2</sup> Azure OpenAI resources (with access to embedding models) that were created in the [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs) aren't supported. Only Azure OpenAI resources created in the Azure portal are compatible with the [Azure OpenAI Embedding skill](cognitive-search-skill-azure-openai-embedding.md).
 
 <sup>3</sup> For billing purposes, you must [attach your Azure AI multi-service resource](cognitive-search-attach-cognitive-services.md) to the skillset in your Azure AI Search service. Unless you use a [keyless connection (preview)](cognitive-search-attach-cognitive-services.md#bill-through-a-keyless-connection) to create the skillset, both resources must be in the same region.
 

@@ -6,7 +6,7 @@ author: haileytap
 ms.author: haileytapia
 ms.service: azure-ai-search
 ms.topic: how-to
-ms.date: 05/08/2025
+ms.date: 06/11/2025
 ms.custom:
   - references_regions
   - ignite-2024
@@ -42,9 +42,9 @@ For illustration purposes, this article uses the [sample health plan PDFs](https
 
 + A skillset with these two skills:
 
-  + [Document Layout skill](cognitive-search-skill-document-intelligence-layout.md) that splits documents based on paragraph boundaries. This skill has region requirements. An Azure AI multi-service resource must be in the same region as Azure AI Search with AI Enrichment.
+  + [Document Layout skill](cognitive-search-skill-document-intelligence-layout.md) that splits documents based on paragraph boundaries. This skill has region requirements. An Azure AI multi-service resource must be in the same region as Azure AI Search with AI enrichment.
 
-  + [Azure OpenAI Embedding skill](cognitive-search-skill-azure-openai-embedding.md) that generates vector embeddings. This skill also has region requirements. The model must be in the same region as Azure AI Search.
+  + [Azure OpenAI Embedding skill](cognitive-search-skill-azure-openai-embedding.md) that generates vector embeddings. This skill *doesn't* have region requirements.
 
 ## Prepare data files
 

@@ -76,7 +76,7 @@ By default, a search service is created with one replica and one partition. You
 
 Semantic ranker increases the cost of running your service. If you don't want to use this feature, you can [disable semantic ranker](semantic-how-to-enable-disable.md) at the service level.
 
-To learn about other features that affect billing, see [How you're charged for Azure AI Search](search-sku-manage-costs.md#how-youre-charged-for-azure-ai-search).
+To learn about other features that affect billing, see [How you're charged for Azure AI Search](search-sku-manage-costs.md#how-youre-charged-for-the-base-service).
 
 ## Enable diagnostic logging
 

@@ -1,112 +1,147 @@
 ---
-title: Plan and manage costs
+title: Plan and Manage Costs
 titleSuffix: Azure AI Search
-description: 'Learn about billable events, the billing model, and tips for cost control when running an Azure AI Search service.'
-
+description: Learn about billable events, the billing model, and tips for cost control when running an Azure AI Search service.
 manager: nitinme
 author: haileytap
 ms.author: haileytapia
 ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
-ms.topic: conceptual
-ms.date: 03/21/2025
+ms.topic: how-to
+ms.date: 06/10/2025
 ---
 
 # Plan and manage costs of an Azure AI Search service
 
-This article explains the billing model and billable events of Azure AI Search, and provides guidance for managing the costs.
+This article explains how Azure AI Search is billed, including fixed and variable costs, and provides guidance for cost management.
 
-As a first step, estimate your baseline costs by using the Azure pricing calculator. Alternatively, estimated costs and tier comparisons can also be found in the [Select a pricing tier](search-create-service-portal.md#choose-a-tier) page when creating a service.
+Before you create a search service, use the [Azure pricing calculator](https://azure.microsoft.com/pricing/calculator/) to estimate costs based on your planned [capacity](search-capacity-planning.md) and features. Another resource is a capacity-planning worksheet that models your expected index size, indexing throughput, and indexing costs.
 
-Azure provides built-in cost management that cuts across service boundaries to provide inclusive cost monitoring and the ability to set budgets and define alerts. The costs of running a search service will vary depending on capacity and which features you use. After you create your search service, optimize capacity so that you pay only for what you need. 
+As your search workload evolves, follow our tips to minimize costs during both deployment and operation. You can also use built-in metrics to monitor query requests and [Cost Management](/azure/cost-management-billing/costs/overview-cost-management) to create budgets, alerts, and data exports.
 
 > [!NOTE]
-> Higher capacity partitions are available at the same billing rate on newer services created after April and May 2024. For more information about partition size upgrades, see [Service limits](search-limits-quotas-capacity.md#service-limits).
+> Higher-capacity partitions are available at the same billing rate on services created after April and May 2024. For more information about partition-size upgrades, see [Service limits](search-limits-quotas-capacity.md#service-limits).
 
 <a name="billable-events"></a>
 
 ## Understand the billing model
 
-Azure AI Search runs on Azure infrastructure that accrues costs when you deploy new resources. It's important to understand that there could be other additional infrastructure costs that might accrue.
+Azure AI Search has both fixed and pay-as-you-go billing. You pay a fixed rate for your search service as long as it exists, while premium features are billed according to your usage.
 
-### How you're charged for Azure AI Search
+Costs for Azure AI Search are only a portion of the monthly costs in your Azure bill. Although this article focuses on planning and managing Azure AI Search costs, you're billed for all Azure services and resources used in your Azure subscription, including non-Microsoft services.
 
-When you create or use Search resources, you're charged for the following meters:
+### How you're charged for the base service
 
-+ You're charged an hourly rate based on the [pricing tier](search-sku-tier.md) of your search service, prorated to the hour.
+When you create or use search resources, you're charged for the minimum required replica and partition combination (R × P) at the prorated hourly rate of your [pricing tier](search-sku-tier.md). As your search units increase or decrease, so do your costs. For more information and an example of the billing model, see [Billing rates](search-sku-tier.md#billing-rates).
 
-+ The charge is applied per the number of search units (SU) allocated to the service. Search units are [units of capacity](search-capacity-planning.md). Total SU is the product of replicas and partitions (R x P = SU) used by your service.
+### How you're charged for premium features
 
-Billing is based on capacity (SUs) and the costs of running premium features, such as [AI enrichment](cognitive-search-concept-intro.md), [semantic ranker](semantic-search-overview.md), and [private endpoints](service-create-private-endpoint.md). Meters associated with premium features are listed in the following table.
+Premium features are charged in addition to the base cost of your search service. The following table lists premium features and their billing units. All of these features are optional, so if you don't use them, you don't incur any charges.
 
-| Meter | Unit |
+| Feature | Billing unit |
 |-------|------|
-| Image extraction (AI enrichment) <sup>1, 2</sup> | Per 1000 images. See the [pricing page](https://azure.microsoft.com/pricing/details/search/#pricing). |
-| Custom Entity Lookup skill (AI enrichment) <sup>1</sup> | Per 1000 text records. See the [pricing page](https://azure.microsoft.com/pricing/details/search/#pricing) |
-| [Built-in skills](cognitive-search-predefined-skills.md)  (AI enrichment) <sup>1</sup> | Number of transactions, billed at the same rate as if you had performed the task by calling Azure AI services directly. You can process 20 documents per indexer per day for free. Larger or more frequent workloads require a multi-resource Azure AI services key. |
-| [Semantic ranker](semantic-search-overview.md) <sup>1</sup> | Number of queries of "queryType=semantic", billed at a progressive rate. See the [pricing page](https://azure.microsoft.com/pricing/details/search/#pricing). |
-| [Shared private link](search-indexer-howto-access-private.md) <sup>1</sup> | [Billed for bandwidth](https://azure.microsoft.com/pricing/details/private-link/) as long as the shared private link exists and is used. |
+| Image extraction (AI enrichment) <sup>1</sup> | Per 1,000 images. See the [pricing page](https://azure.microsoft.com/pricing/details/search/#pricing). |
+| [Custom Entity Lookup skill](cognitive-search-skill-custom-entity-lookup.md) (AI enrichment) | Per 1,000 text records. See the [pricing page](https://azure.microsoft.com/pricing/details/search/#pricing) |
+| [Built-in or custom skills](cognitive-search-predefined-skills.md) (AI enrichment) <sup>2</sup> | Number of transactions. Billed at the rate of the model provider: Azure AI services, Azure OpenAI, or Azure AI Foundry. |
+| [Vectorizers](vector-search-how-to-configure-vectorizer.md) <sup>2</sup> | Number of vectorization operations. Billed at the rate of the model provider: Azure AI Vision, Azure OpenAI, or Azure AI Foundry. |
+| [Semantic ranker](semantic-search-overview.md) | Number of queries of `queryType=semantic`. Billed at a progressive rate. See the [pricing page](https://azure.microsoft.com/pricing/details/search/#pricing). |
+| [Shared private link](search-indexer-howto-access-private.md) | [Billed for bandwidth](https://azure.microsoft.com/pricing/details/private-link/) as long as the shared private link exists and is used. |
 
-<sup>1</sup> Applies only if you use or enable the feature.
+<sup>1</sup> Refers to images extracted from a file within the indexer pipeline. Text extraction is free. Image extraction is billed when you [enable the `indexAction` parameter](cognitive-search-concept-image-scenarios.md#configure-indexers-for-image-processing) or when you call the [Document Extraction skill](cognitive-search-skill-document-extraction.md).
 
-<sup>2</sup> Refers to images extracted from a file within the indexer pipeline. Text extraction is free. Image extraction is billed during the initial document cracking step and when invoking the Document Extraction skill. In an [indexer configuration](/rest/api/searchservice/indexers/create#indexer-parameters), `imageAction` is the parameter that triggers image extraction. If `imageAction` is set to "none" (the default), there's no charge. If set to "generateNormalizedImages" or "generateNormalizedImagePerPage" and the document contains images, you're charged for each image. This is true even if there are no skills to consume the image content.
+<sup>2</sup> Charges for Azure OpenAI models and Azure AI Foundry models appear on your bill for those services.
 
-You aren't billed on the number of full text or vector queries, query responses, or documents ingested, although [service limits](search-limits-quotas-capacity.md) do apply at each tier.
+### How you're otherwise charged
 
-Data traffic might also incur networking costs. See the [Bandwidth pricing](https://azure.microsoft.com/pricing/details/bandwidth/).
+Depending on your configuration and usage, the following charges might apply:
 
-Several premium features such as [knowledge store](knowledge-store-concept-intro.md), [debug sessions](cognitive-search-debug-session.md), and [enrichment cache](cognitive-search-incremental-indexing-conceptual.md) have a dependency on Azure Storage. The meters for Azure Storage apply in this case, and the associated storage costs of using these features are included in the Azure Storage bill.
++ Data traffic might incur networking costs. See the [bandwidth pricing](https://azure.microsoft.com/pricing/details/bandwidth/).
 
-[Customer-managed keys](search-security-manage-encryption-keys.md) provide double encryption of sensitive content. This feature requires a billable [Azure Key Vault](https://azure.microsoft.com/pricing/details/key-vault/)).
++ Several premium features, such as [knowledge stores](knowledge-store-concept-intro.md), [debug sessions](cognitive-search-debug-session.md), and [enrichment caches](cognitive-search-incremental-indexing-conceptual.md), depend on Azure Storage and incur storage costs. Charges for these features appear on your Azure Storage bill.
 
-Skillsets can include [billable built-in skills](cognitive-search-predefined-skills.md), non-billable built-in utility skills, and custom skills. Non-billable utility skills include Conditional, Shaper, Text Merge, Text Split. You aren't charged for using them. There's no API key requirement, and no 20 document limit. 
++ [Customer-managed keys](search-security-manage-encryption-keys.md), which provide double encryption of sensitive content, require a billable [Azure Key Vault](https://azure.microsoft.com/pricing/details/key-vault/).
 
-A custom skill is functionality you provide. The cost of using a custom skill depends entirely on whether custom code is calling other billable services.  There's no API key requirement and no 20 document limit on custom skills.
++ A skillset can include [billable built-in skills](cognitive-search-predefined-skills.md), nonbillable built-in utility skills, and custom skills. Nonbillable utility skills include [Conditional](cognitive-search-skill-conditional.md), [Shaper](cognitive-search-skill-shaper.md), [Text Merge](cognitive-search-skill-textmerger.md), and [Text Split](cognitive-search-skill-textsplit.md). They don't have an API key requirement or 20-document limit.
 
-## Monitor costs
++ A custom skill is functionality you provide. Custom skills are billable only if they call other billable services. They don't have an API key requirement or 20-document limit.
+
+> [!NOTE]
+> You aren't billed for the number of full-text or vector queries, query responses, or documents ingested. However, [service limits](search-limits-quotas-capacity.md) apply to each pricing tier.
+
+## Estimate and plan costs
+
+Use the [Azure pricing calculator](https://azure.microsoft.com/pricing/calculator/) to estimate your baseline costs for Azure AI Search. You can also  find estimated costs and tier comparisons on the [Select Pricing Tier](search-create-service-portal.md#choose-a-tier) page during service creation.
 
-Cost management is built into the Azure infrastructure. Review [Billing and cost management](/azure/cost-management-billing/cost-management-billing-overview) for more information about tracking costs, tools, and APIs.
+For initial testing, we recommend that you create a capacity-planning worksheet. The worksheet helps you understand the index-to-source ratio and the effect of enrichment or vector features on both capacity and cost.
+
+To create a capacity-planning worksheet:
+
+1. Index a small sample (1–5%) of your data. Include any [OCR](cognitive-search-skill-ocr.md), enrichment, or embedding skills you plan to use.
+
+1. Measure the index size, indexing throughput, and indexing costs.
+
+1. Extrapolate the results to estimate the full-scale requirements for your data.
 
 ## Minimize costs
 
-Follow these guidelines to minimize costs of an Azure AI Search solution.
+To minimize the costs of your Azure AI Search solution, use the following strategies:
+
+### Deployment and configuration
 
-1. If possible, create a search service [in a region that has more storage per partition](search-limits-quotas-capacity.md#service-limits). If you're using multiple Azure resources in your solution, create them in the same region, or in as few regions as possible, to minimize or eliminate bandwidth charges.
++ Create a search service in a [region with more storage per partition](search-limits-quotas-capacity.md#service-limits).
 
-1. [Scale up](search-capacity-planning.md) for resource-intensive operations like indexing, and then readjust downwards for regular query workloads. If there are predictable patterns to your workloads, you might be able to synchronize scale up to coincide with the expected volume (you would need to write code to automate this).
++ Create all related Azure resources in the same region (or as few regions as possible) to minimize or eliminate bandwidth charges.
 
-   When estimating the cost of a search solution, keep in mind that pricing and capacity aren't linear (doubling capacity more than doubles the cost on the same tier). Also, at some point, switching up to a higher tier can give you better and faster performance at roughly the same price point. For more information and an example, see [Switch to a Standard S2 tier](search-performance-tips.md#tip-switch-to-a-standard-s2-tier).
++ Choose the lightest [pricing tier](search-sku-tier.md) that meets your needs. Basic and S1 offer full access to the modern API at the lowest hourly rate per SU.
 
-1. Consider [Azure Web App](/azure/app-service/overview) for your front-end application so that requests and responses stay within the data center boundary.
++ Use [Azure Web Apps](/azure/app-service/overview) for your front-end application to keep requests and responses within the data center boundary.
 
-1. If you're using [AI enrichment](cognitive-search-concept-intro.md), there's an extra charge for blob storage, but the cumulative cost goes down if you enable [enrichment caching](cognitive-search-incremental-indexing-conceptual.md).
+### Scaling
+
++ [Add partitions](search-capacity-planning.md#add-or-remove-partitions-and-replicas) only when the index size or ingestion throughput requires it.
+
++ [Add replicas](search-capacity-planning.md#add-or-remove-partitions-and-replicas) only when your queries per second increase, when complex queries are throttling your service, or when high availability is required.
+
++ Scale up for resource-intensive operations, such as indexing, and then readjust downwards for regular query workloads.
+
++ Write code to automate scaling for predictable workload patterns.
+
++ Remember that capacity and pricing aren't linear. Doubling capacity more than doubles costs on the same tier. For better performance at a similar price, consider [switching to a higher tier](search-performance-tips.md#tip-switch-to-a-standard-s2-tier).
+
+### Indexing and enrichment
+
++ Use [incremental indexing](search-howto-reindex.md) to process only new or changed data.
+
++ Use [enrichment caching](cognitive-search-incremental-indexing-conceptual.md) and a [knowledge store](knowledge-store-concept-intro.md) to reuse previously enriched content. Although caching incurs a storage charge, it lowers the cumulative cost of [AI enrichment](cognitive-search-concept-intro.md).
+
++ Keep vector payloads compact. For vector search, see the [vector  compression best practices](https://techcommunity.microsoft.com/blog/azure-ai-services-blog/azure-ai-search-cut-vector-costs-up-to-92-5-with-new-compression-techniques/4404866).
+
+## Monitor costs
 
-## Create budgets
+At the service level, you can [monitor built-in metrics](search-monitor-queries.md) for your queries per second (QPS), search latency, throttled queries, and index size. You can then [create an Azure Monitor dashboard](/azure/azure-monitor/visualize/tutorial-logs-dashboards) that overlays QPS, latency, and cost data to determine when to add or remove replicas.
 
-You can create [budgets](/azure/cost-management-billing/costs/tutorial-acm-create-budgets?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn) to manage costs and create [alerts](/azure/cost-management-billing/costs/cost-mgt-alerts-monitor-usage-spending?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn) that automatically notify stakeholders of spending anomalies and overspending risks. Alerts are based on spending compared to budget and cost thresholds. Budgets and alerts are created for Azure subscriptions and resource groups, so they're useful as part of an overall cost monitoring strategy. 
+At the subscription or resource group level, [Cost Management](/azure/cost-management-billing/costs/overview-cost-management) provides tools to track, analyze, and control costs. You can use Cost Management to:
 
-Budgets can be created with filters for specific resources or services in Azure if you want more granularity present in your monitoring. Filters help ensure that you don't accidentally create new resources that cost you extra money. For more information about the filter options available when you create a budget, see [Group and filter options](/azure/cost-management-billing/costs/group-filter?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn).
++ [Create budgets](/azure/cost-management-billing/costs/tutorial-acm-create-budgets?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn) that define and track progress against spending limits. For more granular monitoring, customize your budgets using [filters](/azure/cost-management-billing/costs/group-filter?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn) for specific Azure resources or services. Filters prevent you from accidentally creating resources that incur extra costs.
 
-## Export cost data
++ [Create alerts](/azure/cost-management-billing/costs/cost-mgt-alerts-monitor-usage-spending?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn) that automatically notify stakeholders of spending anomalies or overspending risks. Alerts are based on spending compared to budget and cost thresholds. Both budgets and alerts are created for subscriptions and resource groups, making them useful for monitoring overall costs.
 
-You can also [export your cost data](/azure/cost-management-billing/costs/tutorial-export-acm-data?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn) to a storage account. This is helpful when you need or others to do more data analysis for costs. For example, a finance team can analyze the data using Excel or Power BI. You can export your costs on a daily, weekly, or monthly schedule and set a custom date range. Exporting cost data is the recommended way to retrieve cost datasets.
++ [Export cost data](/azure/cost-management-billing/costs/tutorial-export-acm-data?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn) to a storage account. This is helpful when you or others need to perform more cost analysis. For example, a finance team can analyze the data using Excel or Power BI. You can export your costs on a daily, weekly, or monthly schedule and set a custom date range. Exporting cost data is the recommended method for retrieving cost datasets.
 
 ## FAQ
 
 **Can I temporarily shut down a search service to save on costs?**
 
-Search runs as a continuous service. Dedicated resources are always operational, allocated for your exclusive use for the lifetime of your service. To stop billing entirely, you must delete the service. Deleting a service is permanent and also deletes its associated data.
+Search runs as a continuous service. Dedicated resources are always operational and allocated for your exclusive use for the lifetime of your service. To stop billing entirely, you must delete the service. Deleting a service is permanent and also deletes its associated data.
 
 **Can I change the billing rate (tier) of an existing search service?**
 
 Existing services can be switched between Basic and Standard (S1, S2, and S3) tiers. Currently, you can only switch from a lower tier to a higher tier, such as going from Basic to S1. For more information, see [Change your pricing tier](search-capacity-planning.md#change-your-pricing-tier).
 
-## Next steps
+## Related content
 
-+ Learn more on how pricing works with Azure AI Search. See [Azure AI Search pricing page](https://azure.microsoft.com/pricing/details/search/).
-+ Learn more about [replicas and partitions](search-sku-tier.md).
-+ Learn [how to optimize your cloud investment with Cost Management](/azure/cost-management-billing/costs/cost-mgt-best-practices?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn).
-+ Learn more about managing costs with [cost analysis](/azure/cost-management-billing/costs/quick-acm-cost-analysis?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn).
-+ Learn about how to [prevent unexpected costs](/azure/cost-management-billing/cost-management-billing-overview?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn).
-+ Take the [Cost Management](/training/paths/control-spending-manage-bills?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn) guided learning course.
++ [Azure AI Search pricing](https://azure.microsoft.com/pricing/details/search/)
++ [Choose a pricing tier for Azure AI Search](search-sku-tier.md)
++ [Optimize your cloud investment with Cost Management](/azure/cost-management-billing/costs/cost-mgt-best-practices?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn)
++ [Quickstart: Start using Cost analysis](/azure/cost-management-billing/costs/quick-acm-cost-analysis?WT.mc_id=costmanagementcontent_docsacmhorizontal_-inproduct-learn)

@@ -8,7 +8,7 @@ author: HeidiSteen
 ms.author: heidist
 ms.service: azure-ai-search
 ms.topic: conceptual
-ms.date: 01/15/2025
+ms.date: 06/11/2025
 ms.custom: references_regions
 ---
 
@@ -49,9 +49,6 @@ Once you sign up, you can immediately use either of these links to access Azure
 
      We recommend Basic for larger data files and more indexes, or Free if your files are less than 50 MB. Basic has more features and storage, but it's billable for the lifetime of the service and it might consume about one third of your available credits if you retain it for the entire trial period.
 
-> [!TIP]
-> Azure AI Search and Azure OpenAI must be in the [same region](search-create-service-portal.md#regions-with-the-most-overlap).
-
 ## Step three: Have a plan for next steps
 
 The trial period can go by quick. Having a plan of action can help you get the most out of your trial subscription. For Azure AI Search, most newer customers and developers are exploring RAG patterns.
@@ -72,37 +69,31 @@ Application frontends are useful if you're prototyping a solution for a wider au
 
 ## 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.
+Azure AI Search offers integrated operations with applied AI in the Azure cloud. For data residency and efficient operations, integration typically depends on services running within the same region.
 
-Start here if you want to use built-in vectorization or chat models:
+> [!NOTE]
+> The same-region requirement doesn't apply to Azure OpenAI and Azure AI Foundry for interoperability with Azure AI Search. However, using the same region can improve performance and reduce latency.
 
-- [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-foundry/reference/region-support)
+For [AI enrichment](cognitive-search-concept-intro.md), [integrated vectorization](vector-search-integrated-vectorization.md), and [multimodal search](multimodal-search-overview.md) powered by Azure AI services, you must create Azure AI Search and Azure AI services multi-service in the same region. This is required for [billing purposes](cognitive-search-attach-cognitive-services.md).
 
-Continue with the following link to confirm region and tier availability for AI Search:
+Before you create these resources:
 
-- [Azure AI Search region list](search-region-support.md). This list identifies region support for Azure AI Search, applied AI (Azure AI services multi-service), and semantic ranking. You don't need a separate region check for applied AI.
++ Check [Azure AI Search regions](search-region-support.md). The **AI enrichment** column indicates whether Azure AI Search and Azure AI services multi-service are in the same region.
 
-> [!TIP]
-> 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**, **West US**, **Switzerland North**, **Korea Central**, **South East Asia**, or **Australia East**.
++ Check [Azure AI Vision regions](/azure/ai-services/computer-vision/overview-image-analysis?tabs=4-0#region-availability). The **Multimodal embeddings** column indicates regional support for the multimodal APIs that enable text and image vectorization. Azure AI Vision provides these APIs, which you access through an Azure AI services multi-service resource. Ensure that your search service and multi-service resource are in the same region as the multimodal APIs.
 
 ### Create services
 
-1. [Create a search service](search-create-service-portal.md) if you don't have one already, choosing the Basic tier and a region that also offers a model provider. Most Azure AI Search regions provide higher capacity storage limits. There are just a few that have older and lower limits. For the Basic tier, as you install, confirm that you have a 15-GB partition.
+1. [Create a search service](search-create-service-portal.md) if you don't have one already. Choose the Basic tier and, if applicable, the same region as Azure AI services multi-service. Most Azure AI Search regions provide higher capacity storage limits. There are just a few that have older and lower limits. For the Basic tier, as you install, confirm that you have a 15-GB partition.
 
    > [!div class="nextstepaction"]
    > [Create a search service](search-create-service-portal.md)
 
-1. [Create an Azure Storage account](/azure/storage/common/storage-account-create?tabs=azure-portal), choosing a general purpose account and using default settings.
+1. [Create an Azure Storage account](/azure/storage/common/storage-account-create?tabs=azure-portal). Choose a general purpose account and use default settings.
 
-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 OpenAI resource](/azure/ai-services/openai/how-to/create-resource?pivots=web-portal).
 
-1. [Create an Azure AI services multi-service account](/azure/ai-services/multi-service-resource#azure-ai-services-resource-for-azure-ai-search-skills?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:
+1. [Create an Azure AI services multi-service resource](/azure/ai-services/multi-service-resource#azure-ai-services-resource-for-azure-ai-search-skills?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 Azure Marketplace.":::
 

@@ -9,7 +9,7 @@ ms.author: mdonovan
 ms.service: azure-ai-search
 ms.custom:
 ms.topic: tutorial
-ms.date: 05/29/2025
+ms.date: 06/11/2025
 
 ---
 
@@ -52,7 +52,7 @@ Using a REST client and the [Search REST APIs](/rest/api/searchservice/) you wil
 + An [Azure AI services multi-service account](/azure/ai-services/multi-service-resource#azure-ai-services-resource-for-azure-ai-search-skills) for image vectorization. Image vectorization requires Azure AI Vision multimodal embeddings. For an updated list of regions, see the [Azure AI Vision documentation](/azure/ai-services/computer-vision/overview-image-analysis#region-availability).
 
 + [Azure AI Search](search-what-is-azure-search.md), with a managed identity. [Create a service](search-create-service-portal.md) or [find an existing service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices) in your current subscription.  
-  > Your service must be on the Basic tier or higher—this tutorial is not supported on the Free tier. Additionally, it must be in the [same region as Azure AI services multi-service](search-create-service-portal.md#regions-with-the-most-overlap).
+  > Your service must be on the Basic tier or higher—this tutorial isn't supported on the Free tier. It must also be in the same region as your multi-service account.
 
 + [Visual Studio Code](https://code.visualstudio.com/download) with a [REST client](https://marketplace.visualstudio.com/items?itemName=humao.rest-client).
 

@@ -9,7 +9,7 @@ ms.author: rawan
 ms.service: azure-ai-search
 ms.custom:
 ms.topic: tutorial
-ms.date: 05/29/2025
+ms.date: 06/11/2025
 
 ---
 
@@ -47,7 +47,7 @@ Using a REST client and the [Search REST APIs](/rest/api/searchservice/), you wi
 
 + An [Azure AI services multi-service account](/azure/ai-services/multi-service-resource#azure-ai-services-resource-for-azure-ai-search-skills) for image vectorization. Image vectorization requires Azure AI Vision multimodal embeddings. For an updated list of regions, see the [Azure AI Vision documentation](/azure/ai-services/computer-vision/overview-image-analysis#region-availability).
 
-+ [Azure AI Search](search-what-is-azure-search.md), with a managed identity. [Create a service](search-create-service-portal.md) or [find an existing service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices) in your current subscription. Your service must be on the Basic tier or higher—this tutorial isn't supported on the Free tier. Additionally, it must be in the [same region as Azure AI services multi-service](search-create-service-portal.md#regions-with-the-most-overlap).
++ [Azure AI Search](search-what-is-azure-search.md), with a managed identity. [Create a service](search-create-service-portal.md) or [find an existing service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices) in your current subscription. Your service must be on the Basic tier or higher—this tutorial isn't supported on the Free tier. It must also be in the same region as your multi-service account.
 
 + [Visual Studio Code](https://code.visualstudio.com/download) with a [REST client](https://marketplace.visualstudio.com/items?itemName=humao.rest-client).
 

@@ -10,7 +10,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2024
 ms.topic: tutorial
-ms.date: 03/11/2025
+ms.date: 06/11/2025
 ---
 
 # Tutorial: Maximize relevance (RAG in Azure AI Search)
@@ -34,9 +34,9 @@ This tutorial updates the search index created by the [indexing pipeline](tutori
 
 - [Visual Studio Code](https://code.visualstudio.com/download) with the [Python extension](https://marketplace.visualstudio.com/items?itemName=ms-python.python) and the [Jupyter package](https://pypi.org/project/jupyter/).
 
-- [Azure AI Search](search-create-service-portal.md), Basic tier or higher for managed identity and semantic ranking, in the same region as Azure OpenAI and Azure AI Services.
+- [Azure AI Search](search-create-service-portal.md), Basic tier or higher for managed identity and semantic ranking.
 
-- [Azure OpenAI](/azure/ai-services/openai/how-to/create-resource), with a deployment of text-embedding-002 and gpt-35-turbo, in the same region as Azure AI Search.
+- [Azure OpenAI](/azure/ai-services/openai/how-to/create-resource), with a deployment of text-embedding-002 and gpt-35-turbo.
 
 ## Download the sample
 

@@ -8,7 +8,7 @@ ms.author: heidist
 ms.service: azure-ai-search
 ms.topic: tutorial
 ms.custom: references_regions
-ms.date: 05/30/2025
+ms.date: 06/11/2025
 
 ---
 
@@ -33,21 +33,11 @@ If you don't have an Azure subscription, create a [free account](https://azure.m
 
 - An **Owner** or **User Access Administrator** role on your Azure subscription, necessary for creating role assignments. You use at least three Azure resources in this tutorial. The connections are authenticated using Microsoft Entra ID, which requires the ability to create roles. Role assignments for connecting to models are documented in this article. If you can't create roles, you can use [API keys](search-security-api-keys.md) instead.
 
-- A model provider, such as [Azure OpenAI](/azure/ai-services/openai/how-to/create-resource), Azure AI Vision via an [Azure AI services multi-service resource](/azure/ai-services/multi-service-resource#azure-ai-services-resource-for-azure-ai-search-skills), or [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs).
+- A model provider, such as [Azure OpenAI](/azure/ai-services/openai/how-to/create-resource), Azure AI Vision via an [Azure AI services multi-service resource](/azure/ai-services/multi-service-resource#azure-ai-services-resource-for-azure-ai-search-skills), or [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs). For Azure AI Vision, ensure that your multi-service resource is in the same region as [Azure AI Search](search-region-support.md) and the [Azure AI Vision multimodal APIs](/azure/ai-services/computer-vision/overview-image-analysis?tabs=4-0#region-availability).
 
   We use Azure OpenAI in this tutorial. Other providers are listed so that you know your options for integrated vectorization.
 
-- Azure AI Search, Basic tier or higher provides a [managed identity](search-howto-managed-identities-data-sources.md) used in role assignments. 
-
-- A shared region. To complete all of the tutorials in this series, the region must support both Azure AI Search and the model provider. See supported regions for:
-
-  - [Azure OpenAI regions](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability)
-
-  - [Azure AI Vision regions](/azure/ai-services/computer-vision/overview-image-analysis?tabs=4-0#region-availability)
-
-  - [Azure AI Foundry regions](/azure/ai-foundry/reference/region-support)
-
-  - [Azure AI Search regions](search-region-support.md)
+- Azure AI Search, Basic tier or higher provides a [managed identity](search-howto-managed-identities-data-sources.md) used in role assignments.
 
 ## Review models supporting built-in vectorization
 

@@ -10,7 +10,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2024
 ms.topic: tutorial
-ms.date: 05/08/2025
+ms.date: 06/11/2025
 ---
 
 # Tutorial: Build an indexing pipeline for RAG on Azure AI Search
@@ -37,9 +37,9 @@ If you don't have an Azure subscription, create a [free account](https://azure.m
 
 - [Azure Storage](/azure/storage/common/storage-account-create) general purpose account. This exercise uploads PDF files into blob storage for automated indexing.
 
-- [Azure AI Search](search-create-service-portal.md), Basic tier or above for managed identity and semantic ranking. Choose a region that's shared with Azure OpenAI and Azure AI Services.
+- [Azure AI Search](search-create-service-portal.md), Basic tier or above for managed identity and semantic ranking. Choose a region that's shared with Azure AI services.
 
-- [Azure OpenAI](/azure/ai-services/openai/how-to/create-resource), with a deployment of text-embedding-3-large, in the same region as Azure AI Search. For more information about embedding models used in RAG solutions, see [Choose embedding models for RAG in Azure AI Search](tutorial-rag-build-solution-models.md).
+- [Azure OpenAI](/azure/ai-services/openai/how-to/create-resource), with a deployment of text-embedding-3-large. For more information about embedding models used in RAG solutions, see [Choose embedding models for RAG in Azure AI Search](tutorial-rag-build-solution-models.md).
 
 - [Azure AI services multi-service account](/azure/ai-services/multi-service-resource#azure-ai-services-resource-for-azure-ai-search-skills), in the same region as Azure AI Search. This resource is used for the Entity Recognition skill that detects locations in your content.
 

@@ -9,7 +9,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2024
 ms.topic: how-to
-ms.date: 04/17/2025
+ms.date: 06/11/2025
 ---
 
 # Create a vector index
@@ -31,7 +31,7 @@ This article explains the workflow using the REST API for illustration. Once you
 
 ## Prerequisites
 
-+ Azure AI Search, in any region and on any tier. If you plan to use [integrated vectorization](vector-search-integrated-vectorization.md), Azure AI Search must be in the same region as the embedding models hosted on Azure OpenAI or in Azure AI Vision.
++ Azure AI Search, in any region and on any tier. If you plan to use [integrated vectorization](vector-search-integrated-vectorization.md) with Azure AI skills and vectorizers, Azure AI Search must be in the same region as the embedding models hosted on Azure AI Vision.
 
 + Your source documents must have [vector embeddings](vector-search-how-to-generate-embeddings.md) to upload to the index. Or, you can use [integrated vectorization](vector-search-integrated-vectorization.md) for this step.
 

@@ -9,7 +9,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 05/21/2025
+ms.date: 06/11/2025
 ---
 
 # Generate embeddings for search queries and documents
@@ -30,7 +30,7 @@ If you want to handle data chunking and vectorization yourself, we provide demos
 
 ## Create resources in the same region
 
-Integrated vectorization usually requires resources to be in the same region:
+Although integrated vectorization with Azure OpenAI embedding models doesn't require resources to be in the same region, using the same region can improve performance and reduce latency.
 
 1. [Check regions for a text embedding model](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability).
 

@@ -9,7 +9,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 05/08/2025
+ms.date: 06/11/2025
 ---
 
 # Integrated vector embedding in Azure AI Search
@@ -76,7 +76,7 @@ The diagram focuses on integrated vectorization, but your solution isn't limited
 
 ## Availability and pricing
 
-Integrated vectorization is available in all regions and tiers. However, if you're using Azure OpenAI and Azure AI skills and vectorizers, make sure your Azure AI services multi-service account is [available in the same regions as Azure AI Search](search-region-support.md).
+Integrated vectorization is available in all regions and tiers. However, if you're using Azure AI skills and vectorizers, make sure your Azure AI services multi-service resource is available in the [same region as Azure AI Search](search-region-support.md).
 
 If you're using a custom skill and an Azure hosting mechanism (such as an Azure function app, Azure Web App, and Azure Kubernetes), check the [Azure product by region page](https://azure.microsoft.com/explore/global-infrastructure/products-by-region/?products=search) for feature availability.