Governance
Production AI governance for Power BI semantic models
SemanticOps adds the governance layer that enterprise teams need before AI and agents touch business-critical semantic models. Choose the layer that matches the problem you are solving.
Policy engine
Enforce governance rules before semantic model operations execute. Block unsafe changes, gate actions, and require validation.
Evaluate policy enforcementAI lockdown modes
Define what assistants and users can inspect, query, modify, or block — by environment, team, and risk level.
Design an AI access modelAudit logging
Tamper-evident records of every MCP tool call, policy decision, and test result during AI-assisted development.
Review audit loggingData masking
Mask PII and sensitive numeric values before query results enter AI context. Enforced at the MCP layer.
Review masking workflowRLS / OLS testing
Validate row-level and object-level security behavior after model changes and AI-assisted edits.
Validate model securityEnterprise controls
The full governance stack for enterprise adoption: policy, lockdown, audit, testing, masking, and rollback.
Evaluate Enterprise controlsHow the layers work together
Lockdown defines the boundary. Policy decides the action. Audit proves the event. Testing validates the outcome. Rollback provides recovery.