@@ -3,22 +3,42 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: include
-ms.date: 01/09/2026
+ms.date: 02/03/2026
 ms.author: lajanuar
 ---
 <!-- markdownlint-disable MD041 -->
 ## Prerequisites
 
 > [!NOTE]
 >
-> * If you already have an Azure Language in Foundry Tools or multi-service resource you can continue to use those existing Language resources within the Microsoft Foundry portal via a Foundry Hub project.
-> * For more information, see [How to use Foundry Tools in the Foundry portal](/azure/ai-services/connect-services-ai-foundry-portal).
+> * If you already have an Azure Language in Foundry Tools or multi-service resource, you can continue to use those existing Language resources within the Microsoft Foundry portal via a Foundry Hub project.
+> * For more information, see [How to use Foundry Tools in the Foundry portal](../../../../connect-services-foundry-portal.md)
 > * We highly recommended that you use a Foundry resource in the Foundry; however, you can also follow these instructions using a Language resource.
 
 <!-- markdownlint-disable MD032 -->
 [!INCLUDE [Foundry prerequisites](../../../includes/microsoft-foundry/prerequisites.md)]
 * A [**Conversational language understanding (CQA)**](../../../conversational-language-understanding/overview.md) or [**Custom question answering (CQA)**](../../../question-answering/overview.md) project created in the Foundry.
 
+## Migrate an existing orchestration workflow from Language Studio
+
+If you have an existing orchestration workflow in Language Studio that you want to use in Foundry, you have two migration options:
+
+### Option 1: Connect your Language resource to a Foundry Hub (recommended)
+
+Connect your existing Language resource to a Foundry Hub project. This approach automatically preserves all task linkages between your orchestration workflow and its associated CLU and CQA tasks.
+
+### Option 2: Import projects into a new Foundry resource
+
+If you want to use a new Foundry resource, import your projects individually. To preserve task linkages, import in the following order:
+
+1. Import your CLU and CQA tasks first.
+1. Import the orchestration workflow only after the dependent tasks are available in the Foundry resource.
+
+> [!IMPORTANT]
+> The import order matters. If you import the orchestration workflow before its dependent CLU and CQA tasks, the task linkages aren't preserved. You must then manually relink the tasks in the **Configure orchestration** section.
+
+For detailed migration steps, see [Migrate from Language Studio to Microsoft Foundry](../../../migration-studio-to-foundry.md).
+
 ## Get started
 
 After you create your Foundry resource, you can initiate an orchestration workflow project in the [Microsoft Foundry](https://ai.azure.com/). This project serves as a dedicated workspace for developing custom machine learning models using your data. Access to the project is restricted to you and others who have permissions for the associated Foundry resource.
@@ -45,7 +65,11 @@ Let's begin:
 
 1. From the window that appears, select **Conversational Orchestration Workflow** as the task type, then select **Next**.
 
-   :::image type="content" source="../../media/select-orchestration-workflow.png" alt-text="Screenshot of selecting orchestration workflow in the Foundry.":::
+    * If you don't have a CLU or CQA fine-tuning task in this Foundry resource, a warning appears indicating that no tasks are available to link.
+
+       :::image type="content" source="../../media/orchestration-no-tasks-warning.png" alt-text="Screenshot of no tasks warning in orchestration workflow creation in the Foundry.":::
+
+    * Create a [Conversational Language Understanding](../../../conversational-language-understanding/quickstart.md) or [Custom Question Answering](../../../question-answering/quickstart/sdk.md) task first, then return to create your orchestration workflow.
 
 1. In the **Create service fine-tuning window**, you can choose to create a new task or import an existing one. Complete all required fields, then select **Create**:
 
@@ -55,23 +79,44 @@ Let's begin:
 
 1. After creating the orchestration workflow project, you'll be directed to the project overview page. Here, you can manage your project settings, monitor training progress, and access various tools to enhance your model.
 
-## Link tasks
+## Configure orchestration
 
-1. To add existing **`CLU`** or **`CQA`** models to your orchestration workflow, navigate to the **Link tasks** button within your project. Here, you can add intents and entities from your existing models to the orchestration workflow.
+Connect your existing **Conversational Language Understanding** (CLU) and **Custom Question Answering** (CQA) fine-tuning tasks to create a unified orchestration layer that routes user inputs to the appropriate model. You can define more routing intents when user inputs are ambiguous and need extra logic to identify the correct task.
+
+> [!NOTE]
+> If the **Configure orchestration** page is empty, you don't have any CLU or CQA fine-tuning tasks in this Foundry resource. Create a [Conversational Language Understanding](../../../conversational-language-understanding/quickstart.md) or [Custom Question Answering](../../../question-answering/quickstart/sdk.md) task first, then return to this page and link it.
+
+1. To add existing **`CLU`** or **`CQA`** models to your orchestration workflow, navigate to your fine-tuning project and select the **Configure orchestration** section from the **Getting started** menu. There, you can link your fine-tuning tasks and add intents from your existing models to the orchestration workflow.
 
    :::image type="content" source="../../media/orchestration-workflow-overview.png" alt-text="Screenshot of orchestration workflow overview in the Foundry." lightbox="../../media/orchestration-workflow-overview.png":::
 
-1. Link your tasks by selecting from the **Task type** and **Fine-tuning task name** dropdown menus. The **Intent name** field automatically populates with the same name as the **fine-tuning task name** field. Once everything is set, select **Add** to continue.
+1. Link your tasks by selecting the radio button next to the task you want to link, and then selecting the **Link fine-tuning task** from the top navigation bar. The **Orchestration intent name** field automatically populates with the same name as the **Fine-tuning task name** field.
+
+   :::image type="content" source="../../media/orchestration-link-tasks.png" alt-text="Screenshot of linking tasks in orchestration workflow in the Foundry." lightbox="../../media/orchestration-link-tasks.png":::
+
+1. Once this step is complete, the status for your linked tasks changes from **Unlinked** to **Linked** in the **Configure orchestration** section.
+
+   :::image type="content" source="../../media/orchestration-linked-tasks.png" alt-text="Screenshot of linked tasks in orchestration workflow in the Foundry." lightbox="../../media/orchestration-linked-tasks.png":::
 
-   :::image type="content" source="../../media/orchestration-link-tasks.png" alt-text="Screenshot of linking tasks in orchestration workflow in the Foundry.":::
+1. To link multiple fine-tuning tasks at once, select one or more unlinked tasks, then select **Link fine-tuning task** from the top navigation bar.
+
+1. To unlink tasks, select one or more linked tasks, then select **Unlink fine-tuning task** from the top navigation bar.
+
+1. To add routing intents, select the **Intents** tab from the top navigation bar. In the window that appears, select the **+ Add intent** button, provide a unique name for your intent in the **Intent name** field, then select **Add** to continue.
+
+   :::image type="content" source="../../media/orchestration-add-intent.png" alt-text="Screenshot of adding intents in orchestration workflow in the Foundry." lightbox="../../media/orchestration-add-intent.png":::
 
 ## Add training data
 
-1. Navigate to the Manage Data tab and add your utterances file. For this project, you can download our [**sample utterances file**](https://github.com/Azure-Samples/cognitive-services-sample-data-files/blob/master/language-service/CLU/clu_utterances.json) which comes preconfigured with labeled utterances.
+1. Navigate to the Manage Data tab. For this project, use one of your existing **Conversational Language Understanding** (CLU) projects. If your existing project doesn't include labeled utterances, you can download our [**sample utterances file**](https://github.com/Azure-Samples/cognitive-services-sample-data-files/blob/master/language-service/CLU/clu_utterances.json) which comes preconfigured with labeled utterances.
+
+1. Select the **Upload utterances** button to upload your utterances file in JSON format.
+
+   :::image type="content" source="../../media/upload-utterances.png" alt-text="Screenshot of uploading utterances in orchestration workflow in the Foundry.":::
 
 1. After uploading your utterances file, select the **unlinked intents** from the Insights pane. This action allows you to map these intents to the appropriate linked tasks within your orchestration workflow.
 
-   :::image type="content" source="../../media/select-unlinked-intents.png" alt-text="Screenshot of unlinked intents in orchestration workflow in the Foundry." lightbox="../../media/select-unlinked-intents.png":::
+   :::image type="content" source="../../media/select-unlinked-intents.png" alt-text="Screenshot of unlinked intents in orchestration workflow in the Foundry.":::
 
 ## Train your model
 

@@ -6,7 +6,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: quickstart
-ms.date: 01/09/2026
+ms.date: 02/03/2026
 ms.author: lajanuar
 ms.custom: language-service-clu, mode-other
 zone_pivot_groups: foundry-rest-api

@@ -1,31 +1,85 @@
 ---
-title: "Migrate to Azure Language in Foundry Tools from: Language Understanding (LUIS), QnA Maker, and Text Analytics"
+title: "Migrate to Azure Language from Language Understanding (LUIS) or QnA Maker"
 titleSuffix: Foundry Tools
 description: Use this article to learn if you need to migrate your applications from Language Understanding (LUIS), QnA Maker, and Text Analytics.
 author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: concept-article
-ms.date: 11/18/2025
+ms.date: 02/09/2026
 ms.author: lajanuar
 ---
-# Migrating to Azure Language in Foundry Tools
+<!-- markdownlint-disable MD025 -->
+# Migrate to Azure Language in Foundry Tools
 
 On November 2, 2021, Azure Language in Foundry Tools was released into public preview. Azure Language unifies the Text Analytics, QnA Maker, and Language Understanding (LUIS) service offerings, and provides several new features as well.
 
-## Do I need to migrate to Azure Language if I'm using Text Analytics?
+> [!IMPORTANT]
+>
+> * You may experience intermittent interruptions when calling the Language Understanding (LUIS) service. Microsoft is in the final phase of retiring LUIS. These interruptions are temporary but expected during this retirement phase.
+> * Beginning March 31, 2026, LUIS runtime and authoring endpoints (including REST API calls) are fully retired, and all LUIS requests fail.
+> * To ensure uninterrupted operation, export all of your LUIS app data as soon as possible in order to:
+>   * Start using [Conversational Language Understanding (CLU)](../conversational-language-understanding/overview.md), or
+>   * Try out a [Microsoft Foundry](../conversational-language-understanding/quickstart.md).
+> * Use the following API to export your data: [LUIS Versions - Export](/rest/api/luis/versions/export?view=rest-luis-v2.0&preserve-view=true&tabs=HTTP).
 
-Text Analytics is incorporated into Azure Language, and its features are still available. If you're using Text Analytics features, your applications should continue to work without breaking changes. If you're using Text Analytics API (v2.x or v3), see the [Text Analytics migration guide](migrate-language-service-latest.md) to migrate your applications to the unified Language endpoint and the latest client library.
+## How do I migrate to Azure Language if I'm using Language Understanding (LUIS)?
 
-Consider using one of the available quickstart articles to see the latest information on service endpoints, and API calls.
+If you're using Language Understanding (LUIS), you can [import your Language Understanding (LUIS) JSON file](../conversational-language-understanding/how-to/fail-over.md#import-to-a-new-project) to the new Conversational language understanding feature:
 
-## How do I migrate to Azure Language if I'm using Language Understanding (LUIS)?
+1. Export the LUIS app
+
+   * Export your LUIS application as JSON by using the LUIS authoring APIs or the LUIS portal.
+   * LUIS Versions – [Export REST API](/rest/api/luis/versions/export?view=rest-luis-v2.0&preserve-view=true&tabs=HTTP)
+
+1. Map LUIS data to the CLU schema
+
+   * Update the exported JSON to align intents, entities, and utterances with the CLU project schema.
+   * [Conversational Language Understanding overview](../conversational-language-understanding/overview.md) provides details on the CLU schema and supported features.
 
-If you're using Language Understanding (Language Understanding (LUIS)), you can [import your Language Understanding (LUIS) JSON file](../conversational-language-understanding/how-to/migrate-from-Language Understanding (LUIS).md) to the new Conversational language understanding feature.
+1. Create a CLU project and import data
+
+   * Create a CLU project and import the prepared data by using Language Studio or the CLU authoring APIs.
+   * [CLU quickstart (REST API)](../conversational-language-understanding/quickstart.md?pivots=rest-api) provides instructions on creating a CLU project and importing data.
+
+1. Train the model
+
+   * Start a training job to build the CLU model from the imported data.
+   * [Train and evaluate a CLU model](../conversational-language-understanding/how-to/train-model.md) provides details on training and evaluating your CLU model.
+
+1. Test the model
+
+   * Send test utterances to the CLU prediction endpoint and verify intent and entity results.
+   * [Conversational Language Understanding overview](../conversational-language-understanding/how-to/call-api.md) provides details on querying your CLU model.
 
 ## How do I migrate to Azure Language if I'm using QnA Maker?
 
-If you're using QnA Maker, see the [migration guide](/previous-versions/azure/ai-services/qnamaker/overview/overview) for information on migrating knowledge bases from QnA Maker to question answering.
+If you're using QnA Maker, you can [import your QnA Maker knowledge base](../question-answering/how-to/migrate-knowledge-base.md#import-a-project) to the custom question answering (CQA) feature:
+
+1. Export the QnA Maker knowledge base
+
+   * Download your knowledge base by using the QnA Maker REST APIs with your endpoint key and knowledge base ID.
+   * [QnA Maker REST API reference](/rest/api/questionanswering/question-answering-projects/export?view=rest-questionanswering-2021-10-01&preserve-view=true&tabs=HTTP) provides instructions on exporting your knowledge base.
+
+1. Create a Custom Question Answering project
+
+   * Create a new Custom Question Answering project.
+   * [Create a Custom Question Answering project](../question-answering/quickstart/sdk.md) provides instructions on creating a CQA project.
+
+1. Import the knowledge base
+
+   * Import the exported knowledge base file into your Custom Question Answering project.
+   * [Import knowledge base](../question-answering/how-to/authoring.md#import-project) provides instructions on importing your knowledge base.
+   * For more information, see also, [Move projects and question answer pairs](../question-answering/how-to/migrate-knowledge-base.md).
+
+1. Create and test a knowledge base
+
+   * Create, test, and deploy a custom question answering knowledge base in the Microsoft Foundry (classic) Language playground.
+   * [Create, test, and deploy: CQA knowledge base](../question-answering/how-to/create-test-deploy.md) provides instructions on creating and testing your project.
+
+
+Consider using one of the available quickstart articles to see the latest information on service endpoints, and API calls.
+
 
 ## See also
 

@@ -816,7 +816,7 @@ items:
           href: ../speech-service/call-center-quickstart.md?context=%2fazure%2fai-services%2flanguage-service%2fcontext%2fcontext
         - name: Ingestion Client
           href: ../speech-service/ingestion-client.md?context=%2fazure%2fai-services%2flanguage-service%2fcontext%2fcontext
-- name: Reference
+- name: API reference
   items:
   - name: REST API
     href: /rest/api/language/
@@ -936,12 +936,12 @@ items:
         href: concepts/encryption-data-at-rest.md
       - name: Compliance and certification
         href: https://azure.microsoft.com/support/legal/cognitive-services-compliance-and-privacy/
-- name: Reference
+- name: Migration and release history
   items:
-    - name: Migrate from LUIS, QnA Maker, and Text Analytics
+    - name: Migrate from LUIS or QnA Maker to Language Service
       displayName: text analytics, luis, qna
       href: reference/migrate.md
-    - name: Migrate from Text Analytics API to Language Service API
+    - name: Migrate from Text Analytics API to Language Service
       displayName: api versions, versioning
       href: reference/migrate-language-service-latest.md
     - name: Azure Language release history

@@ -6,14 +6,26 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: whats-new
-ms.date: 01/14/2026
+ms.date: 02/09/2026
 ms.author: lajanuar
 ---
 <!-- markdownlint-disable MD025 -->
 # What's new in Azure Language in Foundry Tools?
 
 Stay informed about recent releases and enhancements designed to help you get the most out of Azure Language capabilities. Azure Language in Foundry Tools is updated on an ongoing basis. Bookmark this page and stay up to date with release notes, feature enhancements, and our newest documentation.
 
+## February 2026
+
+* **Text PII detection quality improvement**. Backend validation for the Phone Number entity type is updated to broaden detection coverage, resulting in improved recall across supported languages. This change is applied at the service level and requires no updates to your API calls or request parameters.
+
+* **Orchestration workflow playground update**. The Foundry playground experience for orchestration workflow introduces a redesigned task-linking interface. The **Schema definition** page previously available in Language Studio is replaced by the **Configure orchestration** page, which provides a streamlined way to associate fine-tuning tasks with an orchestration workflow task. For more information, see the [Orchestration workflow quickstart](orchestration-workflow/quickstart.md).
+
+* **Language Studio retirement**. Azure Language Studio is scheduled for retirement on **March 20, 2027**. After that date, the Language Studio portal is no longer accessible, but your existing projects, data, and service endpoints remain unaffected. All features and new enhancements are available in Microsoft Foundry. For step-by-step migration instructions, see [Migrate from Language Studio to Microsoft Foundry](migration-studio-to-foundry.md).
+
+* **Foundry (classic) Language playground card is generally available**. The Language playground card in [Microsoft Foundry (classic)](https://ai.azure.com/) exits preview and is now generally available. You can access all Language authoring, testing, and deployment capabilities directly from the playground without any feature restrictions.
+
+* **LUIS migration guidance**. To migrate from **LUIS** to [Conversational Language Understanding (CLU)](conversational-language-understanding/overview.md), see [Migrating to Azure Language in Foundry Tools](reference/migrate.md) for the latest instructions.
+
 ## January 2026
 
 * **Orchestration workflow available in [Microsoft Foundry (classic)](https://ai.azure.com/)**. [Orchestration workflow](orchestration-workflow/quickstart.md) is now supported in Microsoft Foundry (classic).