Define, enforce, and prove governance policy across entitlements, AI systems, control coverage, risk, and audit evidence.
Define who can access what data, under which policy, for what purpose, for how long, and with which approvals.
Operationalize policies through access decisions, masking rules, filters, approval flows, and evidence.
Register and govern AI systems, models, prompts, agents, RAG pipelines, training data, vendors, risks, approvals, and evidence.
Evaluate prompt behavior, retrieval quality, policy checks, drift signals, incidents, and control performance.
Map data and AI risks to controls, policies, owners, exceptions, mitigation plans, testing, and evidence.
Capture audit trails, policy decisions, approvals, classification changes, AI reviews, tests, incidents, and governance actions.
Map obligations and frameworks to controls, owners, policies, testing, and evidence.
Reduced manual governance handoffs with policy-backed request routing and evidence capture.
Yes. Access can be governed at runtime using policy, identity, purpose, sensitivity, ownership, and approval context.