Controlled AI governance from system inventory through evidence-backed decision.
The platform maintains a traceable record across organizations, AI systems, assessments, evidence, mapped controls, risk decisions, remediation and report issuance.
An operating system for controlled AI governance.
AI system registry
Ownership, lifecycle, provider, intended use, criticality and jurisdictional context.
Framework crosswalk
Map one internal control to multiple external requirement references while reusing the same evidence record.
Evidence assurance
Artifact lineage, file hashes, versioning, verification state, reviewer decisions and evidence confidence.
Risk & findings
Residual exposure, remediation plans, due dates, exception handling and escalation.
Continuous governance
Policies, third parties, incidents, change history and reassessment triggers.
Controlled reporting
Versioned report IDs, methodology references, scope boundaries, limitations and integrity hashes.
One evidence model behind multiple frameworks.
Organizations should not upload the same artifact repeatedly for equivalent governance requirements. AIGR stores the control conclusion once and maps that record to applicable frameworks and sector overlays.