Governance adapts to the interaction
AI data governance must operate at runtime when AI systems retrieve
live enterprise data and take actions on it.
Understand the request
Identify the user or AI agent, the business entity in scope, the task, and the intended action.
Determine what is permitted
Evaluate permissions, enterprise policy, consent, privacy, and task boundaries for the request.
Enforce throughout execution
Apply controls across data access, masking, tool use, actions, and write-back as the interaction runs.
Data access
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Scope data to the relevant entity and task
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Restrict records and fields
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Mask sensitive values dynamically
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Tokenize sensitive data before it reaches the LLM
- Enforce consent and privacy requirements
Actions
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Control which tools and operations may run
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Authorize actions by task, user or agent
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Govern transactional write-back
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Require approval or block actions when needed
- Record every action and authorization decision for audit
AI-Ready Data Products
Turn fragmented enterprise data into reusable, entity-centric data products that provide the governed, business-fresh foundation AI needs.
- Unify structured and unstructured data by business entity
- Keep context synchronized with source systems
- Expose governed data and actions via tools and interfaces
- Support both retrieval and authorized write-back
AI Runtime Governance
- Scope data access to the specific entity and task
- Apply masking, privacy, and consent controls in flight
- Control which tools and actions can be invoked
- Govern authorized write-back to enterprise systems
