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AI Governance brings together the AI models used across your connected cloud and AI platforms. Explore which models are in use, how many tokens they consume, their estimated cost, and the people or applications calling them. Track upcoming model retirements to plan transitions and reduce the risk of disruption. Open AI Governance from the main navigation to explore three tabs: Token Usage, Models In Use, and Principals.

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Token usage

The Token Usage tab shows token consumption over time, broken down into input, output, cache read, and cache write tokens. Use the chart to identify which models drive usage and when consumption changes. Switch between This Month and Last Month, and filter by vendor to narrow the view.

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Models in use

The Models In Use tab lists discovered models with their usage, estimated cost, calling principals, and lifecycle status. Models with no usage in the selected period remain visible. Select a model to review its attributes, lifecycle timeline, and token usage, including invocation counts.

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Lifecycle status

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Principals

The Principals tab shows the identities calling your models, along with their token consumption, models used, estimated cost, and last activity. Identity visibility depends on the provider and the access configured for your integration.

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Supported providers

Connect a supported provider to discover models and collect usage data. Estimated costs, where available, are based on published model pricing.

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Identity attribution

Identity attribution links model usage to the person or workload making each call.
  • AWS Bedrock: Calling identities are attributed automatically once AWS is connected.
  • Azure AI Foundry: Token usage and estimated cost are collected through the integration. Calling identity attribution additionally requires diagnostic logging and Microsoft Graph permissions. See Enable AI model identity attribution in the Azure integration guide.
Draftt’s lifecycle policies evaluate AI models against vendor end-of-life dates and version currency. You can also create custom policies using AI model attributes to apply your organization’s standards. See Governance policies.