@@ -1214,4 +1214,3 @@ That's it! In this article, you learned concepts and workflows for downloading,
 * [Document Intelligence container configuration settings](configuration.md)
 
 * [Azure container instance recipe](../../../ai-services/containers/azure-container-instance-recipe.md)
-

@@ -1,23 +1,23 @@
 ---
 title: Regional support for Azure AI Language
 titleSuffix: Azure AI services
-description: Learn which Azure regions are supported by the Language service.
+description: Learn which Azure regions support by the Language service features and capabilities.
 author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: conceptual
-ms.date: 04/29/2025
+ms.date: 09/17/2025
 ms.author: lajanuar
-ms.custom: references_regions 
+ms.custom: references_regions
 ---
 
 # Language service supported regions
 
-The Language service is available for use in several Azure regions. Use this article to learn about the regional support and limitations. 
+The Language service is available for use in several Azure regions. Use this article to learn about the regional support and limitations.
 
-## Region support overview 
+## Region support overview
 
-Typically you can refer to the [region support](https://azure.microsoft.com/explore/global-infrastructure/products-by-region/?products=cognitive-services) for details, and most Language service capabilities are available in all supported regions. Some Language service capabilities, however, are only available in select regions which are listed below. 
+Typically you can refer to the [region support](https://azure.microsoft.com/explore/global-infrastructure/products-by-region/?products=cognitive-services) for details, and most Language service capabilities are available in all supported regions. Some Language service capabilities, however, are only available in select regions.
 
 > [!NOTE]
 > Language service doesn't store or process customer data outside the region you deploy the service instance in.
@@ -28,155 +28,169 @@ Conversational language understanding and orchestration workflow are only availa
 
 | Region             | Authoring | Prediction  |
 |--------------------|-----------|-------------|
-| Australia East     | ✓         | ✓           |
-| Brazil South       |           | ✓           |
-| Canada Central     | ✓         | ✓           |
-| Canada East        |           | ✓           |
-| Central India      | ✓         | ✓           |
-| Central US         |           | ✓           |
-| China East 2       | ✓         | ✓           |
-| China North 2      |           | ✓           |
-| East Asia          |           | ✓           |
-| East US            | ✓         | ✓           |
-| East US 2          | ✓         | ✓           |
-| France Central     |           | ✓           |
-| Germany West Central|           | ✓           |
-| Italy North        |           | ✓           |
-| Japan East         |           | ✓           |
-| Japan West         |           | ✓           |
-| Jio India Central  |           | ✓           |
-| Jio India West     |           | ✓           |
-| Korea Central      |           | ✓           |
-| North Central US   |           | ✓           |
-| North Europe       | ✓         | ✓           |
-| Norway East        |           | ✓           |
-| Qatar Central      |           | ✓           |
-| South Africa North |           | ✓           |
-| South Central US   | ✓         | ✓           |
-| Southeast Asia     |           | ✓           |
-| Sweden Central     |           | ✓           |
-| Switzerland North  | ✓         | ✓           |
-| UAE North          |           | ✓           |
-| UK South           | ✓         | ✓           |
-| UK West            |           | ✓           |
-| West Central US    |           | ✓           |
-| West Europe        | ✓         | ✓           |
-| West US            |            | ✓           |
-| West US 2          | ✓         | ✓           |
-| West US 3          | ✓         | ✓           |
-
-## Custom named entity recognition 
+|AustraliaEast|✓|✓|
+|BrazilSouth||✓|
+|CanadaCentral|✓|✓|
+|CanadaEast||✓|
+|CentralIndia|✓|✓|
+|CentralUS||✓|
+|ChinaEast2|✓|✓|
+|ChinaNorth2||✓|
+|EastAsia||✓|
+|EastUS|✓|✓|
+|EastUS2|✓|✓|
+|FranceCentral||✓|
+|GermanyWestCentral||✓|
+|ItalyNorth||✓|
+|JapanEast||✓|
+|JapanWest||✓|
+|JioIndiaCentral||✓|
+|JioIndiaWest||✓|
+|KoreaCentral||✓|
+|NorthCentralUS||✓|
+|NorthEurope|✓|✓|
+|NorwayEast||✓|
+|QatarCentral||✓|
+|SouthAfricaNorth||✓|
+|SouthCentralUS|✓|✓|
+|SoutheastAsia||✓|
+|SwedenCentral||✓|
+|SwitzerlandNorth|✓|✓|
+|UAENorth||✓|
+|UKSouth|✓|✓|
+|UKWest||✓|
+|WestCentralUS||✓|
+|WestEurope|✓|✓|
+|WestUS||✓|
+|WestUS2|✓|✓|
+|WestUS3|✓|✓|
+
+## Custom named entity recognition
 
 Custom named entity recognition is only available in some Azure regions. Some regions are available for **both authoring and prediction**, while other regions are **prediction only**. Language resources in authoring regions allow you to create, edit, train, and deploy your projects. Language resources in prediction regions allow you to get [predictions from a deployment](./custom-features/multi-region-deployment.md).
 
 | Region             | Authoring | Prediction  |
 |--------------------|-----------|-------------|
-| Australia East     | ✓         | ✓           |
-| Brazil South       |           | ✓           |
-| Canada Central     | ✓         | ✓           |
-| Canada East        |           | ✓           |
-| Central India      | ✓         | ✓           |
-| Central US         |           | ✓           |
-| East Asia          |           | ✓           |
-| East US            | ✓         | ✓           |
-| East US 2          | ✓         | ✓           |
-| France Central     |           | ✓           |
-| Germany West Central|           | ✓           |
-| Japan East         |           | ✓           |
-| Japan West         |           | ✓           |
-| Jio India Central  |           | ✓           |
-| Jio India West     |           | ✓           |
-| Korea Central      |           | ✓           |
-| North Central US   |           | ✓           |
-| North Europe       | ✓         | ✓           |
-| Norway East        |           | ✓           |
-| Qatar Central      |           | ✓           |
-| South Africa North |           | ✓           |
-| South Central US   | ✓         | ✓           |
-| Southeast Asia     |           | ✓           |
-| Sweden Central     |           | ✓           |
-| Switzerland North  | ✓         | ✓           |
-| UAE North          |           | ✓           |
-| UK South           | ✓         | ✓           |
-| UK West            |           | ✓           |
-| West Central US    |           | ✓           |
-| West Europe        | ✓         | ✓           |
-| West US            |            | ✓           |
-| West US 2          | ✓         | ✓           |
-| West US 3          | ✓         | ✓           |
-
+|AustraliaEast|✓|✓|
+|BrazilSouth||✓|
+|CanadaCentral|✓|✓|
+|CanadaEast||✓|
+|CentralIndia|✓|✓|
+|CentralUS||✓|
+|EastAsia||✓|
+|EastUS|✓|✓|
+|EastUS2|✓|✓|
+|FranceCentral||✓|
+|GermanyWestCentral||✓|
+|JapanEast||✓|
+|JapanWest||✓|
+|JioIndiaCentral||✓|
+|JioIndiaWest||✓|
+|KoreaCentral||✓|
+|NorthCentralUS||✓|
+|NorthEurope|✓|✓|
+|NorwayEast||✓|
+|QatarCentral||✓|
+|SouthAfricaNorth||✓|
+|SouthCentralUS|✓|✓|
+|SoutheastAsia||✓|
+|SwedenCentral||✓|
+|SwitzerlandNorth|✓|✓|
+|UAENorth||✓|
+|UKSouth|✓|✓|
+|UKWest||✓|
+|WestCentralUS||✓|
+|WestEurope|✓|✓|
+|WestUS||✓|
+|WestUS2|✓|✓|
+|WestUS3|✓|✓|
+
+### Data augmentation feature in Custom Named Entity Recognition
+
+The data augmentation capability allows users to use an Azure OpenAI model to generate supplementary training data during the creation of a custom named entity recognition model. This functionality is currently limited to select regions.
+
+* All entity data utilized with data augmentation is required to include a description field.
+* Supported Azure OpenAI model types for this feature are gpt-4o and gpt-4 32k.
+* The language resource must also have the **Azure OpenAI Contributor** role assigned on the Azure OpenAI resource.
+
+
+| Region | `CNER` data augmentation support|
+|---|---|
+|EastUS|✓|
+|SwitzerlandNorth|✓|
+|AustraliaEast|✓|
 
 ## Custom text classification
 
 Custom text classification is only available in some Azure regions. Some regions are available for **both authoring and prediction**, while other regions are **prediction only**. Language resources in authoring regions allow you to create, edit, train, and deploy your projects. Language resources in prediction regions allow you to get [predictions from a deployment](./custom-features/multi-region-deployment.md).
 
 | Region             | Authoring | Prediction  |
 |--------------------|-----------|-------------|
-| Australia East     | ✓         | ✓           |
-| Brazil South       |           | ✓           |
-| Canada Central     | ✓         | ✓           |
-| Canada East        |           | ✓           |
-| Central India      | ✓         | ✓           |
-| Central US         |           | ✓           |
-| East Asia          |           | ✓           |
-| East US            | ✓         | ✓           |
-| East US 2          | ✓         | ✓           |
-| France Central     |           | ✓           |
-| Germany West Central|           | ✓           |
-| Japan East         |           | ✓           |
-| Japan West         |           | ✓           |
-| Jio India Central  |           | ✓           |
-| Jio India West     |           | ✓           |
-| Korea Central      |           | ✓           |
-| North Central US   |           | ✓           |
-| North Europe       | ✓         | ✓           |
-| Norway East        |           | ✓           |
-| Qatar Central      |           | ✓           |
-| South Africa North |           | ✓           |
-| South Central US   | ✓         | ✓           |
-| Southeast Asia     |           | ✓           |
-| Sweden Central     |           | ✓           |
-| Switzerland North  | ✓         | ✓           |
-| UAE North          |           | ✓           |
-| UK South           | ✓         | ✓           |
-| UK West            |           | ✓           |
-| West Central US    |           | ✓           |
-| West Europe        | ✓         | ✓           |
-| West US            |            | ✓           |
-| West US 2          | ✓         | ✓           |
-| West US 3          | ✓         | ✓           |
+|AustraliaEast|✓|✓|
+|BrazilSouth||✓|
+|CanadaCentral|✓|✓|
+|CanadaEast||✓|
+|CentralIndia|✓|✓|
+|CentralUS||✓|
+|EastAsia||✓|
+|EastUS|✓|✓|
+|EastUS2|✓|✓|
+|FranceCentral||✓|
+|GermanyWestCentral||✓|
+|JapanEast||✓|
+|JapanWest||✓|
+|JioIndiaCentral||✓|
+|JioIndiaWest||✓|
+|KoreaCentral||✓|
+|NorthCentralUS||✓|
+|NorthEurope|✓|✓|
+|NorwayEast||✓|
+|QatarCentral||✓|
+|SouthAfricaNorth||✓|
+|SouthCentralUS|✓|✓|
+|SoutheastAsia||✓|
+|SwedenCentral||✓|
+|SwitzerlandNorth|✓|✓|
+|UAENorth||✓|
+|UKSouth|✓|✓|
+|UKWest||✓|
+|WestCentralUS||✓|
+|WestEurope|✓|✓|
+|WestUS||✓|
+|WestUS2|✓|✓|
+|WestUS3|✓|✓|
 
 ## Summarization
 
 |Region                |Text abstractive summarization|Conversation summarization               |
 |----------------------|------------------------------|-----------------------------------------|
-|US Gov Virginia       |✓                             |✓                                        |
-|US Gov Arizona        |✓                             |✓                                        |
-|Australia East        |✓                             |✓                                        |
-|Canada Central        |✓                             |✓                                        |
-|Central US            |✓                             |✓                                        |
-|China North 3         |✓                             |✓                                        |
-|East US               |✓                             |✓                                        |
-|East US 2             |✓                             |✓                                        |
-|France Central        |✓                             |✓                                        |
-|Germany West Central  |✓                             |✓                                        |
-|Italy North           |✓                             |✓                                        |
-|Japan East            |✓                             |✓                                        |
-|North Central US      |✓                             |✓                                        |
-|North Europe          |✓                             |✓                                        |
-|South Central US      |✓                             |✓                                        |
-|South UK              |✓                             |✓                                        |
-|Southeast Asia        |✓                             |✓                                        |
-|Switzerland North     |✓                             |✓                                        |
-|USNat East            |✓                             |✓                                        |
-|USNat West            |✓                             |✓                                        |
-|USSec East            |✓                             |✓                                        |
-|USSec West            |✓                             |✓                                        |
-|West Europe           |✓                             |✓                                        |
-|West US               |✓                             |✓                                        |
-|West US 2             |✓                             |✓                                        |
+|AustraliaEast|✓|✓|
+|CanadaCentral|✓|✓|
+|CentralUS|✓|✓|
+|ChinaNorth3|✓|✓|
+|EastUS|✓|✓|
+|EastUS2|✓|✓|
+|FranceCentral|✓|✓|
+|GermanyWestCentral|✓|✓|
+|ItalyNorth|✓|✓|
+|JapanEast|✓|✓|
+|NorthCentralUS|✓|✓|
+|NorthEurope|✓|✓|
+|SouthCentralUS|✓|✓|
+|SouthUK|✓|✓|
+|SoutheastAsia|✓|✓|
+|SwitzerlandNorth|✓|✓|
+|USGovVirginia|✓|✓|
+|USGovArizona|✓|✓|
+|USNatEast|✓|✓|
+|USNatWest|✓|✓|
+|USSecEast|✓|✓|
+|USSecWest|✓|✓|
+|WestEurope|✓|✓|
+|WestUS|✓|✓|
+|WestUS2|✓|✓|
 
 ### Next steps
 
 * [Language support](./language-support.md)
-* [Quotas and limits](./data-limits.md) 
+* [Quotas and limits](./data-limits.md)

@@ -5,7 +5,7 @@ ms.service: azure-ai-language
 ms.topic: how-to
 author: laujan
 ms.author: lajanuar
-ms.date: 06/25/2025
+ms.date: 09/15/2025
 ms.custom: language-service-question-answering
 ---
 
@@ -27,7 +27,7 @@ Before you can set up your resources, you need:
 
 * **An active Azure subscription**. If you don't have one, you can [create one for free](https://azure.microsoft.com/free/cognitive-services).
 * **Requisite permissions**. Make sure the person establishing the account and project is assigned as the Azure AI Account Owner role at the subscription level. Alternatively, having either the **Contributor** or **Cognitive Services Contributor** role at the subscription scope also meets this requirement. For more information, *see* [Role based access control (RBAC)](../../../openai/how-to/role-based-access-control.md#cognitive-services-contributor).
-* An [Azure AI Foundry multi-service resource](../../../multi-service-resource.md) or an [Azure AI Language resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.CognitiveServicesTextAnalytics).
+* An [Azure AI Foundry resource](../../../multi-service-resource.md) or an [Azure AI Language resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.CognitiveServicesTextAnalytics).
 
 * An [Azure OpenAI resource](https://portal.azure.com/#create/Microsoft.CognitiveServicesOpenAI) (optional but required for [option 2](#option-2-configure-azure-language-resource-and-azure-openai-resources))
 

@@ -6,7 +6,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: how-to
-ms.date: 07/23/2025
+ms.date: 09/15/2025
 ms.author: lajanuar
 ms.custom: language-service-clu
 ---
@@ -26,7 +26,7 @@ A Conversational Language Understanding (CLU) fine-tuning task is a workspace pr
 
 * An Azure subscription. If you don't have one, you can [create one for free](https://azure.microsoft.com/free/cognitive-services).
 * **Requisite permissions**. Make sure the person establishing the account and project is assigned as the Azure AI Account Owner role at the subscription level. Alternatively, having either the **Contributor** or **Cognitive Services Contributor** role at the subscription scope also meets this requirement. For more information, *see* [Role based access control (RBAC)](../../../openai/how-to/role-based-access-control.md#cognitive-services-contributor).
-*  An [Azure AI Foundry multi-service resource](../../../multi-service-resource.md). For more information, *see* [Configure an Azure AI Foundry resource](configure-azure-resources.md#option-1-configure-an-azure-ai-foundry-resource). Alternately, you can use an [Azure AI Language resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.CognitiveServicesTextAnalytics).
+*  An [Azure AI Foundry resource](../../../multi-service-resource.md). For more information, *see* [Configure an Azure AI Foundry resource](configure-azure-resources.md#option-1-configure-an-azure-ai-foundry-resource). Alternately, you can use an [Azure AI Language resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.CognitiveServicesTextAnalytics).
 * A Foundry project created in the Azure AI Foundry. For more information, *see* [Create an AI Foundry project](../../../../ai-foundry/how-to/create-projects.md).
 
 ## Create a CLU fine-tuning task project
@@ -47,7 +47,7 @@ A Conversational Language Understanding (CLU) fine-tuning task is a workspace pr
 
    :::image type="content" source="../media/fine-tune-button.png" alt-text="Screenshot of fine-tune button in the Azure AI Foundry.":::
 
-1. From the **Create service fine-tuning** window, choose the **Conversational language understanding** tab and then select **Next**.
+1. From the **Create service fine-tuning** window, choose the **Conversational language understanding** tab, and then select **Next**.
 
    :::image type="content" source="../media/select-project.png" alt-text="Screenshot of conversational language understanding tab in the Azure AI Foundry.":::
 

@@ -3,7 +3,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: include
-ms.date: 08/03/2025
+ms.date: 09/15/2025
 ms.author: lajanuar
 ---
 
@@ -21,7 +21,7 @@ Use this article to get started with Conversational Language understanding using
 
 * **Azure subscription**. If you don't have one, you can [create one for free](https://azure.microsoft.com/free/cognitive-services).
 * **Requisite permissions**. Make sure the person establishing the account and project is assigned as the Azure AI Account Owner role at the subscription level. Alternatively, having either the **Contributor** or **Cognitive Services Contributor** role at the subscription scope also meets this requirement. For more information, *see* [Role based access control (RBAC)](/azure/ai-foundry/openai/how-to/role-based-access-control#cognitive-services-contributor).
-*  [Azure AI Foundry multi-service resource](/azure/ai-services/multi-service-resource). For more information, *see* [Configure an Azure AI Foundry resource](../../how-to/configure-azure-resources.md#option-1-configure-an-azure-ai-foundry-resource). Alternately, you can use an [Azure AI Language resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.CognitiveServicesTextAnalytics).
+*  [Azure AI Foundry resource](/azure/ai-services/multi-service-resource). For more information, *see* [Configure an Azure AI Foundry resource](../../how-to/configure-azure-resources.md#option-1-configure-an-azure-ai-foundry-resource). Alternately, you can use an [Azure AI Language resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.CognitiveServicesTextAnalytics).
 * A Foundry project created in the Azure AI Foundry. For more information, *see* [Create an AI Foundry project](/azure/ai-foundry/how-to/create-projects).
 
 ## Get started with Azure AI Foundry
@@ -36,15 +36,15 @@ Let's begin:
 1. If you aren't already signed in, the portal prompts you to do so with your Azure credentials.
 1. Once signed in, you can create or access your existing projects within Azure AI Foundry.
 1. If you're not already at your project for this task, select it.
-1. On the left side navigation pane, select **Playgrounds**, navigate to the **Language playground card**, and then choose the **Try the Language playground** button.
+1. On the left side navigation pane, select **Playgrounds**, navigate to the **Language playground tile**, and then choose the **Try the Language playground** button.
 
   :::image type="content" source="../../media/quickstarts/try-playground.png" alt-text="Screenshot of the Try Language Playground selection in Azure AI Foundry.":::
 
 ## Try the Language playground
 
 The top section of the Language playground is where you can view and select the available Language services. 
 
-1. Select the **Conversational language understanding** card.
+1. Select the **Conversational language understanding** tile.
 
     :::image type="content" source="../../media/quickstarts/language-playground.png" alt-text="Screenshot of the language playground homepage in Azure AI Foundry.":::
 
@@ -54,7 +54,7 @@ The top section of the Language playground is where you can view and select the
 
 1. From **Create service fine-tuning** window, choose the **Conversational language understanding** card. Then select **Next**.
 
-    :::image type="content" source="../../media/quickstarts/select-project.png" alt-text="Screenshot of conversational language understanding selection card in the Azure AI Foundry.":::
+    :::image type="content" source="../../media/quickstarts/select-project.png" alt-text="Screenshot of conversational language understanding selection tile in the Azure AI Foundry.":::
 
 1. In **Create CLU fine tuning task** window, select **Import an existing project**, then choose your **Connected service** from the drop-down menu and complete the **Name** field.
 

@@ -3,13 +3,13 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: include
-ms.date: 06/30/2025
+ms.date: 09/15/2025
 ms.author: lajanuar
 ---
 
 ## Clean up resources
 
-If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
+To clean up and remove an Azure AI resource, you can delete either the individual resource or the entire resource group. If you delete the resource group, all resources contained within are also deleted.
 
 * [Azure portal](../../multi-service-resource.md?pivots=azportal#clean-up-resources)
 * [Azure CLI](../../multi-service-resource.md?pivots=azcli#clean-up-resources)

@@ -6,7 +6,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: quickstart
-ms.date: 08/20/2025
+ms.date: 09/15/2025
 ms.author: lajanuar
 ms.devlang: csharp
 # ms.devlang: csharp, java, javascript, python
@@ -55,7 +55,7 @@ zone_pivot_groups: programming-languages-text-analytics
 
 ## Clean up resources
 
-If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
+To clean up and remove an Azure AI resource, you can delete either the individual resource or the entire resource group. If you delete the resource group, all resources contained within are also deleted.
 
 * [Azure portal](../../multi-service-resource.md?pivots=azportal#clean-up-resources)
 * [Azure CLI](../../multi-service-resource.md?pivots=azcli#clean-up-resources)

@@ -6,7 +6,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: quickstart
-ms.date: 02/17/2025
+ms.date: 09/15/2025
 ms.author: lajanuar
 ms.devlang: csharp
 # ms.devlang: csharp, java, javascript, python
@@ -55,7 +55,7 @@ zone_pivot_groups: programming-languages-text-analytics
 
 ## Clean up resources
 
-If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
+To clean up and remove an Azure AI resource, you can delete either the individual resource or the entire resource group. If you delete the resource group, all resources contained within are also deleted.
 
 * [Azure portal](../../multi-service-resource.md?pivots=azportal#clean-up-resources)
 * [Azure CLI](../../multi-service-resource.md?pivots=azcli#clean-up-resources)

@@ -6,7 +6,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: quickstart
-ms.date: 05/23/2025
+ms.date: 09/15/2025
 ms.author: lajanuar
 ms.devlang: csharp
 # ms.devlang: csharp, java, javascript, python
@@ -55,7 +55,7 @@ zone_pivot_groups: programming-languages-text-analytics
 
 ## Clean up resources
 
-If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
+To clean up and remove an Azure AI resource, you can delete either the individual resource or the entire resource group. If you delete the resource group, all resources contained within are also deleted.
 
 * [Azure portal](../../multi-service-resource.md?pivots=azportal#clean-up-resources)
 * [Azure CLI](../../multi-service-resource.md?pivots=azcli#clean-up-resources)

@@ -8,38 +8,38 @@ manager: nitinme
 ms.reviewer: cahann, hazemelh
 ms.service: azure-ai-language
 ms.topic: tutorial
-ms.date: 06/21/2025
+ms.date: 09/15/2025
 ---
 
 # Connect different services with Orchestration workflow
 
-Orchestration workflow is a feature that allows you to connect different projects from LUIS, conversational language understanding, and custom question answering in one project. You can then use this project for predictions under one endpoint. The orchestration project makes a prediction on which project should be called and automatically routes the request to that project, and returns with its response. 
+Orchestration workflow is a feature that allows you to connect different projects from conversational language understanding and custom question answering in one project. You can then use this project for predictions under one endpoint. The orchestration project makes a prediction on which project should be called and automatically routes the request to that project, and returns with its response. 
 
-In this tutorial, you will learn how to connect a custom question answering knowledge base with a conversational language understanding project. You will then call the project using the .NET SDK sample for orchestration.
+In this tutorial, you learn how to connect a custom question answering knowledge base with a conversational language understanding project. You then call the project using the .NET SDK sample for orchestration.
 
-This tutorial will include creating a **chit chat** knowledge base and **email commands** project. Chit chat will deal with common niceties and greetings with static responses. Email commands will predict among a few simple actions for an email assistant. The tutorial will then teach you to call the Orchestrator using the SDK in a .NET environment using a sample solution. 
+This tutorial includes creating a **chit chat** knowledge base and **email commands** project. Chit chat deals with common niceties and greetings with static responses. Email commands predict among a few simple actions for an email assistant. The tutorial then teaches you to call the Orchestrator using the SDK in a .NET environment using a sample solution. 
 
 
 ## Prerequisites
 
 - Create a [Language resource](https://portal.azure.com/#create/Microsoft.CognitiveServicesTextAnalytics) **and select the custom question answering feature** in the Azure portal to get your key and endpoint. After it deploys, select **Go to resource**.
-  - You will need the key and endpoint from the resource you create to connect your bot to the API. You'll paste your key and endpoint into the code below later in the tutorial. Copy them from the **Keys and Endpoint** tab in your resource.
+  - You need the key and endpoint from the resource you create to connect your bot to the API. You paste your key and endpoint into the code later in the tutorial. Copy them from the **Keys and Endpoint** tab in your resource.
   - When you enable custom question answering, you must select an Azure search resource to connect to.
-  - Make sure the region of your resource is supported by [conversational language understanding](../../conversational-language-understanding/service-limits.md#regional-availability).
+  - Make sure the region of your resource supports [conversational language understanding](../../conversational-language-understanding/service-limits.md#regional-availability).
 - Download the **OrchestrationWorkflowSample** [sample](https://aka.ms/orchestration-sample).
 
 ## Create a custom question answering knowledge base
 
 1. Sign into the [Language Studio](https://language.cognitive.azure.com/) and select your Language resource. 
-2. Find and select the [Custom question answering](https://language.cognitive.azure.com/questionAnswering/projects/) card in the homepage.
+2. Find and select the [Custom question answering](https://language.cognitive.azure.com/questionAnswering/projects/) tile in the homepage.
 3. Select **Create new project** and add the name **chitchat** with the language _English_ before clicking on **Create project**.
 4. When the project loads, select **Add source** and select _Chit chat_. Select the professional personality for chit chat before
     
     :::image type="content" source="../media/chit-chat.png" alt-text="A screenshot of the chit chat popup." lightbox="../media/chit-chat.png":::
     
 5. Go to **Deploy knowledge base** from the left pane and select **Deploy** and confirm the popup that shows up.
 
-You are now done with deploying your knowledge base for chit chat. You can explore the type of questions and answers to expect in the **Edit knowledge base** page.
+You're now done with deploying your knowledge base for chit chat. You can explore the type of questions and answers to expect in the **Edit knowledge base** page.
 
 ## Create a conversational language understanding project
 
@@ -49,15 +49,15 @@ You are now done with deploying your knowledge base for chit chat. You can explo
     
     :::image type="content" source="../media/import-export.png" alt-text="A screenshot showing where to import a J son file." lightbox="../media/import-export.png":::
     
-4. Once the project is loaded, select **Training jobs** on the left. Press on Start a training job, provide the model name **v1** and press Train.
+4. Once the project is loaded, select **Training jobs**. Press on Start a training job, provide the model name **v1** and press Train.
     
     :::image type="content" source="../media/train-model.png" alt-text="A screenshot of the training page." lightbox="../media/train-model.png":::
     
-5. Once training is complete, click to **Deploying a model** on the left. Select **Add Deployment** and create a new deployment with the name **Testing**, and assign model **v1** to the deployment.
+5. Once training is complete, select to **Deploying a model** on the left. Select **Add Deployment** and create a new deployment with the name **Testing**, and assign model **v1** to the deployment.
     
     :::image type="content" source="../media/deploy-model-tutorial.png" alt-text="A screenshot showing the model deployment page." lightbox="../media/deploy-model-tutorial.png":::
     
-You are now done with deploying a conversational language understanding project for email commands. You can explore the different commands in the **Data labeling** page.
+You're now done with deploying a conversational language understanding project for email commands. You can explore the different commands in the **Data labeling** page.
 
 ## Create an Orchestration workflow project 
 
@@ -70,12 +70,12 @@ You are now done with deploying a conversational language understanding project
 
 5. Add another intent but now select **Question Answering** as the service and select **chitchat** as the project name. 
 6. Similar to conversational language understanding, go to **Training jobs** and start a new training job with the name **v1** and press Train.
-7. Once training is complete, click to **Deploying a model** on the left. Select **Add deployment** and create a new deployment with the name **Testing**, and assign model **v1** to the deployment and press Next.
-8. On the next page, select the deployment name **Testing** for the **EmailIntent**. This tells the orchestrator to call the **Testing** deployment in **EmailProject** when it routes to it. Custom question answering projects only have one deployment by default. 
+7. Once training is complete, select to **Deploying a model** on the left. Select **Add deployment** and create a new deployment with the name **Testing**, and assign model **v1** to the deployment and press Next.
+8. On the next page, select the deployment name **Testing** for the **EmailIntent**. This command tells the orchestrator to call the **Testing** deployment in **EmailProject** when it routes to it. Custom question answering projects only have one deployment by default. 
 
 :::image type="content" source="../media/deployment-orchestrator-tutorial.png" alt-text="A screenshot of the deployment popup for orchestration workflow." lightbox="../media/deployment-orchestrator-tutorial.png":::
 
-Now your orchestration project is ready to be used. Any incoming request will be routed to either **EmailIntent** and the **EmailProject** in conversational language understanding or **ChitChatIntent** and the **chitchat** knowledge base.
+Now your orchestration project is ready to be used. Any incoming request is routed to either **EmailIntent** and the **EmailProject** in conversational language understanding or **ChitChatIntent** and the **chitchat** knowledge base.
 
 ## Call the orchestration project with the Conversations SDK
 
@@ -95,15 +95,15 @@ Uri endpoint = new Uri("{endpoint}");
 AzureKeyCredential credential = new AzureKeyCredential("{api-key}");
 ```
 
-4. Replace the project and deployment parameters to **Orchestrator** and **Testing** as below if they are not set already.
+4. Replace the project and deployment parameters to **Orchestrator** and **Testing** if they aren't set already.
 
 ```csharp
 string projectName = "Orchestrator";
 string deploymentName = "Testing";
 ```
 
 5. Run the project or press F5 in Visual Studio. 
-6. Input a query such as "read the email from matt" or "hello how are you". You'll now observe different responses for each, a conversational language understanding **EmailProject** response from the first query, and the answer from the **chitchat** knowledge base for the second query.
+6. Input a query such as "read the email from matt" or "hello how are you." You now observe different responses for each, a conversational language understanding **EmailProject** response from the first query, and the answer from the **chitchat** knowledge base for the second query.
 
 **Conversational Language Understanding**:
 :::image type="content" source="../media/clu-response-orchestration.png" alt-text="A screenshot showing the sample response from conversational language understanding." lightbox="../media/clu-response-orchestration.png":::

@@ -6,7 +6,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: how-to
-ms.date: 07/17/2025
+ms.date: 09/15/2025
 ms.author: lajanuar
 ms.custom: language-service-pii
 ---
@@ -323,7 +323,7 @@ You receive a 200 (Success) response with JSON output. The **status** field indi
 
 ## Clean up resources
 
-If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
+To clean up and remove an Azure AI resource, you can delete either the individual resource or the entire resource group. If you delete the resource group, all resources contained within are also deleted.
 
 * [Azure portal](../../../multi-service-resource.md?pivots=azportal#clean-up-resources)
 * [Azure CLI](../../../multi-service-resource.md?pivots=azcli#clean-up-resources)

@@ -1762,6 +1762,64 @@ The following entities are listed via country and/or region:
    :::column-end:::
 :::row-end:::
 
+### Sweden
+
+:::row:::
+    :::column span="":::
+        **Entity**
+
+        Sweden National ID
+
+    :::column-end:::
+    :::column span="2":::
+        **Details**
+
+        To get this entity category, add `SENationalID` to the `piiCategories` parameter. `SENationalID` will be returned in the API response if detected.
+
+    :::column-end:::
+    :::column span="":::
+      **Supported languages**
+
+      `en`, `es`, `fr`, `de`, `it`, `pt-pt`, `pt-br`, `zh`, `ja`, `ko`, `nl`, `sv`, `tr`, `hi`, `da`, `nl`, `no`, `ro`, `ar`, `bg`, `hr`, `ms`, `ru`, `sl`, `cs`, `et`, `fi`, `he`, `hu`, `lv`, `sk`, `th`, `uk`
+
+   :::column-end:::
+:::row-end:::
+:::row:::
+    :::column span="":::
+
+        Sweden Passport Number
+
+    :::column-end:::
+    :::column span="2":::
+
+        To get this entity category, add `SEPassportNumber` to the `piiCategories` parameter. `SEPassportNumber` will be returned in the API response if detected.
+
+        Also returned with `domain=phi`.
+    :::column-end:::
+    :::column span="":::
+
+      `en`, `es`, `fr`, `de`, `it`, `pt-pt`, `pt-br`, `zh`, `ja`, `ko`, `nl`, `sv`, `tr`, `hi`, `da`, `nl`, `no`, `ro`, `ar`, `bg`, `hr`, `ms`, `ru`, `sl`, `cs`, `et`, `fi`, `he`, `hu`, `lv`, `sk`, `th`, `uk`
+
+   :::column-end:::
+:::row-end:::
+:::row:::
+    :::column span="":::
+
+        Sweden Tax Identification Number
+
+    :::column-end:::
+    :::column span="2":::
+
+        To get this entity category, add `SETaxIdentificationNumber` to the `piiCategories` parameter. `SETaxIdentificationNumber` will be returned in the API response if detected.
+
+    :::column-end:::
+    :::column span="":::
+
+      `en`, `es`, `fr`, `de`, `it`, `pt-pt`, `pt-br`, `zh`, `ja`, `ko`, `nl`, `sv`, `tr`, `hi`, `da`, `nl`, `no`, `ro`, `ar`, `bg`, `hr`, `ms`, `ru`, `sl`, `cs`, `et`, `fi`, `he`, `hu`, `lv`, `sk`, `th`, `uk`
+
+   :::column-end:::
+:::row-end:::
+
 ### Switzerland
 
 :::row:::

@@ -6,7 +6,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: quickstart
-ms.date: 05/23/2025
+ms.date: 09/15/2025
 ms.author: lajanuar
 ms.devlang: csharp
 # ms.devlang: csharp, java, javascript, python
@@ -57,7 +57,7 @@ zone_pivot_groups: programming-languages-text-analytics
 
 ## Clean up resources
 
-If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
+To clean up and remove an Azure AI resource, you can delete either the individual resource or the entire resource group. If you delete the resource group, all resources contained within are also deleted.
 
 * [Azure portal](../../multi-service-resource.md?pivots=azportal#clean-up-resources)
 * [Azure CLI](../../multi-service-resource.md?pivots=azcli#clean-up-resources)

@@ -5,7 +5,7 @@ ms.service: azure-ai-language
 ms.topic: how-to
 author: laujan
 ms.author: lajanuar
-ms.date: 06/24/2025
+ms.date: 09/15/2025
 ms.custom: language-service-question-answering
 ---
 
@@ -21,7 +21,7 @@ Before you can set up your resources, you need:
 
 * **An active Azure subscription**. If you don't have one, you can [create one for free](https://azure.microsoft.com/free/cognitive-services).
 * **Requisite permissions**. Make sure the person establishing the account and project is assigned as the Azure AI Account Owner role at the subscription level. Alternatively, having either the **Contributor** or **Cognitive Services Contributor** role at the subscription scope also meets this requirement. For more information, *see* [Role based access control (RBAC)](../../../openai/how-to/role-based-access-control.md#cognitive-services-contributor).
-*   An [Azure AI Foundry multi-service resource](../../../multi-service-resource.md) or an [Azure AI Language resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.CognitiveServicesTextAnalytics).
+*   An [Azure AI Foundry resource](../../../multi-service-resource.md) or an [Azure AI Language resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.CognitiveServicesTextAnalytics).
 *   An [Azure AI Search resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.Search) (required for accessing CQA)
 
 

@@ -1,99 +1,127 @@
 ---
-title: Create, test, and deploy your custom question answering project
-description: You can create a custom question answering project from your own content, such as FAQs or product manuals. This article includes an example of creating a custom question answering project from a simple FAQ webpage, to answer questions.
+title: Create, test, and deploy your custom question answering (CQA) knowledge base
+description: You can create a custom question answering knowledge from your own content, such as FAQs or product manuals. This article includes an example of creating a custom question answering knowledge base.
 ms.service: azure-ai-language
 ms.topic: how-to
 author: laujan
 ms.author: lajanuar
-ms.date: 06/04/2025
+ms.date: 09/15/2025
 ms.custom: language-service-question-answering, mode-other
 ---
 
-# Create, test, and deploy a custom question answering project
+# Create, test, and deploy: CQA knowledge base
 
-You can create a custom question answering project from your own content, such as FAQs or product manuals. This article includes an example of creating a custom question answering project from a product manual, to answer questions.
+This guide walks you through the essential steps needed to create, test, and deploy a custom question answering (CQA) knowledge base in the Azure AI Foundry. Whether you're transitioning from Language Studio or starting from scratch, this guide is for you. It provides clear and actionable instructions to achieve a fast and successful CQA deployment in the Azure AI Foundry.
+
+> [!NOTE]
+>
+> * If you already have an Azure AI Language or multi-service resource—whether used on its own or through Language Studio—you can continue to use those existing Language resources within the Azure AI Foundry portal. For more information, see [How to use Azure AI services in the Azure AI Foundry portal](/azure/ai-services/connect-services-ai-foundry-portal).
+> * In Azure AI Foundry, a fine-tuning task serves as your workspace for your CQA solutions. Previously, a **fine-tuning task** was referred to as a **CQA project**. You might encounter both terms used interchangeably in older CQA documentation.
+> * We highly recommend that you use an Azure AI Foundry resource in the AI Foundry; however, you can also follow these instructions using a Language resource.
+>
 
 ## Prerequisites
 
-> [!div class="checklist"]
-> * If you don't have an Azure subscription, create a [free account](https://azure.microsoft.com/free/cognitive-services/) before you begin.
-> * A [language resource](https://aka.ms/create-language-resource) with the custom question answering feature enabled.
+Before you get started, you need the following resources and permissions:
+
+* **An active Azure subscription**. If you don't have one, [create one for free](https://azure.microsoft.com/free/cognitive-services).
+* **Requisite permissions**. Make sure the person establishing the account and project is assigned as the Azure AI Account Owner role at the subscription level. Alternatively, having either the **Contributor** or **Cognitive Services Contributor** role at the subscription scope also meets this requirement. For more information, *see* [Role based access control (RBAC)](../../../openai/how-to/role-based-access-control.md#cognitive-services-contributor).
+*   An [Azure AI Foundry resource](../../../multi-service-resource.md) or an [Azure AI Language resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.CognitiveServicesTextAnalytics).
+*   An [Azure AI Search resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.Search) (required for accessing CQA). For more information on how to connect your Azure AI Search resource, *see* [Configure connections in AI Foundry](../../conversational-language-understanding/how-to/configure-azure-resources.md#step-2-configure-connections-in-ai-foundry)
+* A Foundry project created in the Azure AI Foundry. For more information, *see* [Create an AI Foundry project](/azure/ai-foundry/how-to/create-projects).
+
+## Get started
+
+1. Navigate to the [Azure AI Foundry](https://ai.azure.com/).
+
+1. If you aren't already signed in, the portal prompts you to do so with your Azure credentials.
+
+1. Once signed in, you can create or access your existing projects within Azure AI Foundry.
+
+1. If you're not already at your project for this task, select it.
+
+## Create your CQA fine tuning task
+
+In the Azure AI Foundry, a fine-tuning task serves as your workspace for your CQA solutions. Previously, a **fine-tuning task** was referred to as a **CQA project**. You might encounter both terms used interchangeably in older CQA documentation.
+
+1. After you select the Azure AI Foundry project to use for this project, select **fine-tuning** from the left navigation menu.
+
+     :::image type="content" source="../media/agents/fine-tuning-selection.png" alt-text="Screenshot of the fine-tuning menu selection in the Azure AI Foundry.":::
+
+1. From the main window, select the **AI Service fine-tuning** tab and then the **+ Fine-tune button**.
+
+     :::image type="content" source="../media/agents/fine-tune-button.png" alt-text="Screenshot of fine-tune button in the Azure AI Foundry.":::
+
+1. From the **Create service fine-tuning** window, choose the **Custom question answering** tab and then select **Next**.
+
+     :::image type="content" source="../media/agents/custom-question-answering-tab.png" alt-text="Screenshot of custom question answering tab in the Azure AI Foundry.":::
+
+1. Select your **Connected Azure AI Search resource** from the **Create CQA fine tuning task** window. For more information, *see* [Configure Azure resource connections](../../conversational-language-understanding/how-to/configure-azure-resources.md#step-2-configure-connections-in-ai-foundry).
 
-## Create your first custom question answering project
+1. Next, complete the **Name** and **Language** fields. For this project, you can leave the **Default answer when no answer is returned** field as is (**No answer found**).
 
-1. Sign in to the [Language Studio](https://language.azure.com/) with your Azure credentials.
+1. Select the **Create** button.
 
-2. Scroll down to **Understand questions and conversational language** and select **Open custom question answering**.
 
-    > [!div class="mx-imgBorder"]
-    > ![Open custom question answering](../media/create-test-deploy/open-custom-question-answering.png)
+## Add a CQA knowledge base source
 
-3. If your resource isn't yet connected to Azure Search select **Connect to Azure Search**. This opens a new browser tab to **Features** pane of your resource in the Azure portal.
+A CQA knowledge base is a structured set of question-and-answer pairs optimized for conversational AI. The knowledge base uses natural language processing to interpret user queries and return context-aware, accurate answers from a specific dataset.
 
-    > [!div class="mx-imgBorder"]
-    > ![Connect to Azure Search](../media/create-test-deploy/connect-to-azure-search.png)
+1. From the **Getting Started** menu, select **Manage sources**.
 
-4. Select **Enable custom question answering**, choose the Azure Search resource to link to, and then select **Apply**.
+     :::image type="content" source="../media/agents/manage-sources.png" alt-text="Screenshot of manage sources selection in the Azure AI Foundry.":::
 
-    > [!div class="mx-imgBorder"]
-    > ![Enable custom question answering](../media/create-test-deploy/enable-custom-question-answering.png)
+1. From the main window, select the **+ Add source** drop-down menu.
 
-5. Return to the Language Studio tab. You might need to refresh this page for it to register the change to your resource. Select **Create new project**.
+1. From the drop-down menu you can select **Add chit chat**, **Add URLs**, or **Add Files**.
 
-6. Choose the option **I want to set the language for all projects created in this resource** > select **English** > Select **Next**.
+     :::image type="content" source="../media/agents/add-source-menu.png" alt-text="Screenshot of add source drop-down menu in the Azure AI Foundry.":::
 
-7. Enter a project name of **Sample-project**, a description of **My first question answering project**, and leave the default answer with a setting of **No answer found**.
+1. For this project, choose **Add URLS**.
 
-8. Review your choices and select **Create project**
+1. In the **Add URLs** window, add the following values:
 
-9. From the **Manage sources** page select **Add source** > **URLS**.
+   * **URL name**: **Surface Book User Guide**
+   * **URL**: **https://download.microsoft.com/download/7/B/1/7B10C82E-F520-4080-8516-5CF0D803EEE0/surface-book-user-guide-EN.pdf** 
+   * **Classify file structure**: Leave the default setting (**Auto-detect**)
 
-10. Select **Add url** enter the following values and then select **Add all**:
+     :::image type="content" source="../media/agents/add-urls.png" alt-text="Screenshot of the select url source selection and add button in the Azure AI Foundry.":::
 
-    |URL Name|URL Value|
-    |--------|---------|
-    |Surface Book User Guide |`https://download.microsoft.com/download/7/B/1/7B10C82E-F520-4080-8516-5CF0D803EEE0/surface-book-user-guide-EN.pdf` |
+1. Finally, select the **Add URLs** button. 
 
-    The extraction process takes a few moments to read the document and identify questions and answers. The service determines if the underlying content is structured or unstructured.
+    The extraction process requires a short amount of time to analyze the document and detect questions and answers. During this step, the service evaluates whether the content is structured or unstructured.<br>
 
-    After successfully adding the source, you can then edit the source contents to add more custom question answer sets.
+    Once the source is successfully added, you can edit its contents and include added custom question-and-answer pairs.
 
-## Test your project
 
-1. Select the link to your source, this will open the edit project page.
+1. Once the source is successfully added, it appears in the **Manage sources** window. There you have the option to edit its contents and include additional custom question-and-answer pairs.
 
-2. Select **Test** from the menu bar > Enter the question **How do I setup my surface book?**. An answer will be generated based on the question answer pairs that were automatically identified and extracted from your source URL:
+     :::image type="content" source="../media/agents/manage-url-sources.png" alt-text="Screenshot of manage sources listing in the Azure AI Foundry.":::
 
-    > [!div class="mx-imgBorder"]
-    > ![Test question chat interface](../media/create-test-deploy/test-question.png)
+## Test your knowledge base
 
-    If you check the box for **include short answer response** you will also see a precise answer, if available, along with the answer passage in the test pane when you ask a question.
+1. Select **Test knowledge base** from the **Getting Started** menu.
 
-3. Select **Inspect** to examine the response in more detail. The test window is used to test your changes to your project before deploying your project.
+1. In the main window,  Enter the question **How do I set up my Surface Book?** and then select the **Run** button. Answers are returned using the question-and-answer pairs that were automatically detected and taken from the source URL:
 
-    > [!div class="mx-imgBorder"]
-    > ![See the confidence interval](../media/create-test-deploy/inspect-test.png)
 
-    From the **Inspect** interface, you can see the level of confidence that this response will answer the question and directly edit a given question and answer response pair.
+    :::image type="content" source="../media/agents/test-knowledge-base.png" alt-text="Screenshot of the inspection interface response in the Azure AI Foundry." lightbox="../media/agents/test-knowledge-base.png":::
 
-## Deploy your project
 
-1. Select the **Deploy** project icon to enter the deploy project menu.
+## Deploy your knowledge base
 
-    > [!div class="mx-imgBorder"]
-    > ![Deploy project](../media/create-test-deploy/deploy-knowledge-base.png)
+Deploying a CQA knowledge base means publishing your curated question-and-answer content as a live, searchable endpoint. This process moves your project from a testing phase to a production environment enabling client applications to use it for various projects and solutions, including chatbots.
 
-    When you deploy a project, the contents of your project move from the `test` index to a `prod` index in Azure Search.
+1. Once your inspection is complete, choose the **Deploy knowledge base** section from the **Getting Started** menu.
 
-2. Select **Deploy** > and then when prompted select **Deploy** again.
+1. Select the **Deploy** button first from the **Deploy knowledge base** main window and then from the **Deploy this project** pop-up window. It takes a few minutes to deploy.
 
-    > [!div class="mx-imgBorder"]
-    > ![Successful deployment](../media/create-test-deploy/successful-deployment.png)
+1. After deployment is complete, your deployed project is listed in the **Deploy knowledge base** window.
 
-    Your project is now successfully deployed. You can use the endpoint to answer questions in your own custom application to answer or in a bot.
+That's it! Your Custom Question Answering (CQA) knowledge base provides a natural language interface to your data, allowing users to interact with information in a conversational manner. By deploying this solution, you can create advanced chatbots and interactive agents that comprehend user questions, supply precise answers, and adjust to changing informational requirements.
 
 ## Clean up resources
 
-If you will not continue to test custom question answering, you can delete the associated resource.
+To clean up and remove an Azure AI subscription, you can delete either the individual resource or the entire resource group. If you delete the resource group, all resources contained within it will also be deleted.
 
 ## Next steps

@@ -0,0 +1,164 @@
+---
+title: Create and deploy a custom question and answering (CQA) agent in Azure AI Foundry
+titleSuffix: Azure AI services
+description: Use this guide to create a CQA Azure AI Foundry agent.
+author: laujan
+ms.author: lajanuar
+manager: nitinme
+ms.service: azure-ai-language
+ms.topic: overview
+ms.date: 09/15/2025
+---
+
+# Create and deploy a CQA agent
+
+This article gives you clear steps and important tips for building and deploying a CQA agent. Whether you're new to this process or updating your skills, this guide helps you set up and launch your agent successfully.
+
+> [!NOTE]
+>
+> * If you already have an Azure AI Language or multi-service resource—whether used on its own or through Language Studio—you can continue to use those existing Language resources within the Azure AI Foundry portal. For more information, see [How to use Azure AI services in the Azure AI Foundry portal](/azure/ai-services/connect-services-ai-foundry-portal).
+> * In Azure AI Foundry, a fine-tuning task serves as your workspace for your CQA solutions. Previously, a **fine-tuning task** was referred to as a **CQA project**. You might encounter both terms used interchangeably in older CQA documentation.
+> * We highly recommend that you use an Azure AI Foundry resource in the AI Foundry; however, you can also follow these instructions using a Language resource.
+>
+
+## Prerequisites
+
+Before you get started, you need the following resources and permissions:
+
+* **An active Azure subscription**. If you don't have one, [create one for free](https://azure.microsoft.com/free/cognitive-services).
+* **Requisite permissions**. Make sure the person establishing the account and project is assigned as the Azure AI Account Owner role at the subscription level. Alternatively, having either the **Contributor** or **Cognitive Services Contributor** role at the subscription scope also meets this requirement. For more information, *see* [Role based access control (RBAC)](../../../openai/how-to/role-based-access-control.md#cognitive-services-contributor).
+*   An [Azure AI Foundry resource](../../../multi-service-resource.md) or an [Azure AI Language resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.CognitiveServicesTextAnalytics).
+*   An [Azure AI Search resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.Search) (required for accessing CQA). For more information on how to connect your Azure AI Search resource, *see* [Configure connections in AI Foundry](../../conversational-language-understanding/how-to/configure-azure-resources.md#step-2-configure-connections-in-ai-foundry)
+* A Foundry project created in the Azure AI Foundry with a **deployed CQA knowledge base**. For more information, *see* [Create and deploy a CQA project](create-test-deploy.md)
+
+## Step 1: Get started
+
+Let's begin:
+
+1. Navigate to the Azure AI Foundry.
+
+1. If you aren't already signed in, the portal prompts you to do so with your Azure credentials.
+
+1. Once signed in, you can create or access your existing projects within Azure AI Foundry.
+
+1. If you're not already in your Foundry project with your deployed CQA knowledge base, select it now.
+
+
+## Step 2: Deploy an OpenAI model in Azure AI Foundry (required)
+
+An OpenAI model serves as the foundational source of intelligence and advanced reasoning for your agent.
+
+1. Select **Models + endpoints** from the **My assets** section of the navigation menu:
+
+   :::image type="content" source="../media/agents/models-endpoints.png" alt-text="Screenshot of the deploy model button menu in Azure AI Foundry.":::
+
+1. From the main window, select the **+ Deploy model** button.
+
+1. Select **Deploy base model** from the drop-down menu.
+
+   :::image type="content" source="../media/agents/deploy-model-button.png" alt-text="Screenshot of the connected resources menu selection in Azure AI Foundry.":::
+
+1. From the **Select a model** window, select the **gpt-4** base model for this project.
+
+   :::image type="content" source="../media/agents/gpt-4-selection.png" alt-text="Screenshot of the select a model selection in Azure AI Foundry.":::
+
+1. Next, select the **Confirm** button.
+
+1. In the **Deploy gpt-4** window, keep the default values and select the **Deploy** button.
+
+   :::image type="content" source="../media/agents/deploy-gpt-4.png" alt-text="Screenshot of the gpt-4 deployment window in Azure AI Foundry.":::
+
+1. Great! The model deployment step is complete.
+
+## Step 3: Connect a custom key (required)
+
+A custom key serves as an enhanced security credential for your agent.
+
+1. Navigate to **Management Center** → **Connected Resources**.
+
+    :::image type="content" source="../media/agents/connected-resources.png" alt-text="Screenshot of Management center navigation menu's connected resources selection in Azure AI Foundry.":::
+
+1. From the main window, select the **+ New connection** button.
+
+1. From the **Add a connection to external assets** window, under **Other resource types**, select **Custom keys**.
+
+    :::image type="content" source="../media/agents/add-custom-keys.png" alt-text="Screenshot of add your custom keys selection in Azure AI Foundry.":::
+
+1. In the **Connect a custom resource** window, configure the connection as follows:
+
+   * **Authentication**. Leave this field set to **Custom** (default).
+
+   * **Custom keys**. Select **+ Add key value pairs** and complete the two fields as follows:
+
+    * **First field**. Complete this field with the following key name:
+
+      ```text
+      Ocp-Apim-Subscription-Key
+
+      ```
+    * **Second field**. Complete this field with the key value from your Azure portal **Azure AI Foundry** or **Azure AI Language** resource used to create your CQA knowledge base. Make sure to check the **is secret** box.
+
+        :::image type="content" source="../media/agents/connect-custom-resource.png" alt-text="Screenshot of the connect a custom resource window in the Azure AI Foundry.":::
+
+    * Next, add a **Connection name**.
+
+    * Finally, select the **Add connection** button.
+
+1. Your new Custom key connection is listed on the **Manage connected resources in this project** page.
+
+1. We now provisioned all the necessary resources to create an agent. Select the **Go to project** button to return to your project with your deployed CQA knowledge base.
+
+    :::image type="content" source="../media/agents/go-to-project.png" alt-text="Screenshot of go to project button in Azure AI Foundry.":::
+
+## Step 4: Create an agent
+
+With your OpenAI deployment and custom key in place, you're ready to begin building your agent, grounded in the knowledge base you chose for this project.
+
+1. From your project's overview page, select **Fine tuning** from the left navigation menu.
+1. In the main window, select the **model name**, created with your deployed CQA knowledge base, from the displayed list.
+1. Select **Deploy knowledge base** from the **Getting started** menu.
+1. Under next steps, select the **Create an agent** button.
+
+   :::image type="content" source="../media/agents/create-agent-button.png" alt-text="Screenshot of the create agent button in Azure AI Foundry.":::
+
+1. In the **Create new CQA agent** window, complete the fields as follows:
+
+   * **AI Foundry Project Name**. The name of your project should already appear in this field by default.
+   * **Deployment Model**. The name of the model that you deployed in [Step 2](#step-2-deploy-an-openai-model-in-azure-ai-foundry-required) should already appear in this field by default.
+   * **Agent Name**. Name your agent (don't use dashes or underscores).
+   * **Custom Connection**. The name of the custom key that you connected in [Step 3](#step-3-connect-a-custom-key-required) should already appear in this field by default.
+1. Select the **Next** button:
+
+   :::image type="content" source="../media/agents/create-new-agent.png" alt-text="Screenshot of create CQA agent window in Azure AI Foundry.":::
+
+1. Review the details of your new agent, and then select the **Create agent** button.
+
+1. Once your agent is successfully created, select the **Try in playground** button.
+
+   :::image type="content" source="../media/agents/review-agent-details.png" alt-text="Screenshot of create CQA agent review and create window in Azure AI Foundry.":::
+
+## Step 5: Test in agents playground
+
+The agents playground provides a sandbox to test and configure a deployed agent—adding knowledge and defining actions—before deploying it to production, all without writing code.
+
+1. From the **Create and debug your agents** window select the **Try in Playground** button.
+
+    :::image type="content" source="../media/agents/create-debug-agent.png" alt-text="Screenshot of the **Create and debug your agents** window and **Try in playground** button in Azure AI Foundry":::
+
+1. Once the agent is successfully uploaded to the playground, you can test it by sending test queries.
+
+      :::image type="content" source="../media/agents/agents-playground.png" alt-text="Screenshot of the agents playground in Azure AI Foundry.":::
+
+
+That's it! The agent creation and deployment processes are complete. You now know how to deploy a CQA agent using your own custom knowledge base.
+
+## Clean up resources
+
+To clean up and remove an Azure AI resource, you can delete either the individual resource or the entire resource group. If you delete the resource group, all resources contained within are also deleted.
+
+## Next Steps
+
+> [!div class="nextstepaction"]
+> [Learn about CQA supported languages](../language-support.md)
+
+

@@ -3,7 +3,7 @@ title: Create, test, and deploy your custom question answering project in Azure
 description: Create a custom question answering project from your own content, such as FAQs or product manuals. This article includes an example of creating a custom question answering project from a simple FAQ webpage, to answer questions.
 ms.service: azure-ai-language
 ms.topic: include
-ms.date: 08/30/2025
+ms.date: 09/15/2025
 ---
 
 This quickstart guides you through the essential steps needed to create, test, and deploy a custom question answering (CQA) project in the Azure AI Foundry. Whether you're transitioning from Language Studio or starting from scratch, this quickstart is for you. It provides clear and actionable instructions to achieve a fast and successful CQA project deployment.
@@ -20,7 +20,7 @@ Before you get started, you need the following resources and permissions:
 
 * **An active Azure subscription**. If you don't have one, [create one for free](https://azure.microsoft.com/free/cognitive-services).
 * **Requisite permissions**. Make sure the person establishing the account and project is assigned as the Azure AI Account Owner role at the subscription level. Alternatively, having either the **Contributor** or **Cognitive Services Contributor** role at the subscription scope also meets this requirement. For more information, *see* [Role based access control (RBAC)](../../../openai/how-to/role-based-access-control.md#cognitive-services-contributor).
-*   An [Azure AI Foundry multi-service resource](../../../multi-service-resource.md) or an [Azure AI Language resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.CognitiveServicesTextAnalytics).
+*   An [Azure AI Foundry resource](../../../multi-service-resource.md) or an [Azure AI Language resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.CognitiveServicesTextAnalytics).
 *   An [Azure AI Search resource](https://portal.azure.com/?Microsoft_Azure_PIMCommon=true#create/Microsoft.Search) (required for accessing CQA). For more information on how to connect your Azure AI Search resource, *see* [Configure connections in AI Foundry](../../conversational-language-understanding/how-to/configure-azure-resources.md#step-2-configure-connections-in-ai-foundry)
 * A Foundry project created in the Azure AI Foundry. For more information, *see* [Create an AI Foundry project](/azure/ai-foundry/how-to/create-projects).
 

@@ -3,7 +3,7 @@ title: "Quickstart: custom question answering"
 description: This quickstart shows you how to create and manage your  custom question answering projects.
 ms.service: azure-ai-language
 ms.topic: quickstart
-ms.date: 08/29/2025
+ms.date: 09/15/2025
 author: laujan
 ms.author: lajanuar
 recommendations: false
@@ -34,7 +34,7 @@ zone_pivot_groups: custom-cqa-quickstart
 
 ## Clean up resources
 
-If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
+To clean up and remove an Azure AI resource, you can delete either the individual resource or the entire resource group. If you delete the resource group, all resources contained within are also deleted.
 
 * [Azure portal](../../../multi-service-resource.md?pivots=azportal#clean-up-resources)
 * [Azure CLI](../../../multi-service-resource.md?pivots=azcli#clean-up-resources)

@@ -6,7 +6,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: how-to
-ms.date: 07/17/2025
+ms.date: 09/15/2025
 ms.author: lajanuar
 ms.custom:
   - language-service-summarization
@@ -444,7 +444,7 @@ You receive a 200 (Success) response with JSON output. The **status** field indi
 
 ## Clean up resources
 
-If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
+To clean up and remove an Azure AI resource, you can delete either the individual resource or the entire resource group. If you delete the resource group, all resources contained within are also deleted.
 
 * [Azure portal](../../../multi-service-resource.md?pivots=azportal#clean-up-resources)
 * [Azure CLI](../../../multi-service-resource.md?pivots=azcli#clean-up-resources)

@@ -6,7 +6,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: quickstart
-ms.date: 08/20/2025
+ms.date: 09/15/2025
 ms.author: lajanuar
 ms.devlang: csharp
 # ms.devlang: csharp, java, javascript, python
@@ -56,7 +56,7 @@ zone_pivot_groups: programming-languages-text-analytics
 
 ## Clean up resources
 
-If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
+To clean up and remove an Azure AI resource, you can delete either the individual resource or the entire resource group. If you delete the resource group, all resources contained within are also deleted.
 
 * [Azure portal](../../multi-service-resource.md?pivots=azportal#clean-up-resources)
 * [Azure CLI](../../multi-service-resource.md?pivots=azcli#clean-up-resources)

@@ -7,7 +7,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: quickstart
-ms.date: 08/20/2025
+ms.date: 09/15/2025
 ms.author: lajanuar
 ms.devlang: csharp
 # ms.devlang: csharp, java, javascript, python
@@ -59,7 +59,7 @@ This article contains Text Analytics for health quickstarts that help with using
 
 ## Clean up resources
 
-If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
+To clean up and remove an Azure AI resource, you can delete either the individual resource or the entire resource group. If you delete the resource group, all resources contained within are also deleted.
 
 * [Azure portal](../../multi-service-resource.md?pivots=azportal#clean-up-resources)
 * [Azure CLI](../../multi-service-resource.md?pivots=azcli#clean-up-resources)

@@ -334,48 +334,46 @@ items:
       - name: Data, privacy, and security
         href: ../../ai-foundry/responsible-ai/language-service/data-privacy.md
         displayName: Data privacy, logging, data retention
-    - name: Prebuilt
+    - name: How-to guides
       items:
-      - name: How-to guides
-        items:
-        - name: Call NER
-          href: named-entity-recognition/how-to-call.md
-        - name: Use skill parameters
-          href: named-entity-recognition/how-to/skill-parameters.md
-        - name: Use containers
-          items:
-          - name: Use Docker containers
-            href: named-entity-recognition/how-to/use-containers.md
-          - name: Configure containers
-            href: concepts/configure-containers.md
-          - name: Use container instances
-            href: ../containers/azure-container-instance-recipe.md?context=/azure/ai-services/language-service/context/context
-          - name: Use containers in disconnected environments
-            href: ../containers/disconnected-containers.md
-          - name: Azure AI containers overview
-            href: ../cognitive-services-container-support.md
-      - name: Concepts
-        items:
-        - name: Recognized entity categories
-          href: named-entity-recognition/concepts/named-entity-categories.md
-        - name: Entity Metadata
-          href: named-entity-recognition/concepts/entity-metadata.md
-        - name: API version mapping
-          href: named-entity-recognition/concepts/ga-preview-mapping.md
-      - name: Tutorials
+      - name: Call NER
+        href: named-entity-recognition/how-to-call.md
+      - name: Use skill parameters
+        href: named-entity-recognition/how-to/skill-parameters.md
+      - name: Use containers
         items:
-        - name: Extract information in Excel using Power Automate
-          href: named-entity-recognition/tutorials/extract-excel-information.md
-          displayName: excel integration, power automate, ner automation, extract entities
+        - name: Use Docker containers
+          href: named-entity-recognition/how-to/use-containers.md
+        - name: Configure containers
+          href: concepts/configure-containers.md
+        - name: Use container instances
+          href: ../containers/azure-container-instance-recipe.md?context=/azure/ai-services/language-service/context/context
+        - name: Use containers in disconnected environments
+          href: ../containers/disconnected-containers.md
+        - name: Azure AI containers overview
+          href: ../cognitive-services-container-support.md
+    - name: Concepts
+      items:
+      - name: Recognized entity categories 🆕
+        href: named-entity-recognition/concepts/named-entity-categories.md
+      - name: Entity Metadata
+        href: named-entity-recognition/concepts/entity-metadata.md
+      - name: API version mapping
+        href: named-entity-recognition/concepts/ga-preview-mapping.md
+    - name: Tutorials
+      items:
+      - name: Extract information in Excel using Power Automate
+        href: named-entity-recognition/tutorials/extract-excel-information.md
+        displayName: excel integration, power automate, ner automation, extract entities
     - name: Custom
       items:
-      - name: Custom NER overview
+      - name: Overview
         href: custom-named-entity-recognition/overview.md
-      - name: Custom NER quickstart
+      - name: Quickstart
         href: custom-named-entity-recognition/quickstart.md
-      - name: Custom NER language support
+      - name: Language support
         href: custom-named-entity-recognition/language-support.md
-      - name: Custom NER FAQ
+      - name: FAQ
         href: custom-named-entity-recognition/faq.md
       - name: How-to guides
         items:
@@ -551,9 +549,12 @@ items:
       - name: Migrate projects from QnA Maker
         href: question-answering/how-to/migrate-qnamaker.md
         displayName: migration, transfer
-      - name: Getting started with custom question answering
+      - name: Create, test, and deploy a knowledge base
         href: question-answering/how-to/create-test-deploy.md
         displayName: knowledge base, test deploy
+      - name: Deploy a CQA agent 🆕
+        href: question-answering/how-to/deploy-agent.md
+        displayName: virtual assistant, chatbot, knowledge base, deployment
       - name: Export/import/refresh
         href: question-answering/how-to/export-import-refresh.md
       - name: Use smart URL refresh