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update naming convention
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learn-pr/wwl-sci/purview-ai-developer-apps/azure-ai-services-protections.yml

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### YamlMime:ModuleUnit
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uid: learn.wwl.purview-ai-developer-apps.azure-ai-services-protections
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title: Enforce protections in Azure AI services and Azure AI Foundry
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title: Enforce protections in Foundry Tools and Microsoft Foundry
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metadata:
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title: Enforce Protections in Azure AI Services and Azure AI Foundry
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description: "Enforce protections in Azure AI services and Azure AI Foundry"
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title: Enforce Protections in Foundry Tools and Microsoft Foundry
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description: "Enforce protections in Foundry Tools and Microsoft Foundry"
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ms.date: 08/26/2025
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author: wwlpublish
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ms.author: riswinto

learn-pr/wwl-sci/purview-ai-developer-apps/includes/azure-ai-services-protections.md

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Apps built with Azure AI services or Azure AI Foundry often connect to sensitive data sources. Without governance, they can generate or share regulated information outside approved boundaries. Microsoft Purview lets you onboard these apps so protections such as data loss prevention (DLP), retention, and eDiscovery apply consistently, even when the app is hosted outside Microsoft 365.
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Apps built with Foundry Tools or Microsoft Foundry often connect to sensitive data sources. Without governance, they can generate or share regulated information outside approved boundaries. Microsoft Purview lets you onboard these apps so protections such as data loss prevention (DLP), retention, and eDiscovery apply consistently, even when the app is hosted outside Microsoft 365.
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## Onboard Azure AI apps to Microsoft Purview
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- Confidential content is used in a generated response
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- Protected data is sent or shared by the app
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You can scope DLP policies to apply to Microsoft Entra-registered apps, including those built with Azure AI services. These policies can audit or block actions such as copying, summarizing, or storing protected content.
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You can scope DLP policies to apply to Microsoft Entra-registered apps, including those built with Foundry Tools. These policies can audit or block actions such as copying, summarizing, or storing protected content.
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If you use DSPM for AI collection policies to capture prompts and responses, you can create DLP rules that inspect the text generated by the app. For example, you could create a policy that detects when a response includes personal identifiers or financial information pulled from a protected SharePoint site.
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