Govern, validate, and gate every AI deployment with accountability mapping, automated compliance scoring, intelligent assurance, and a safety gate that blocks unsafe releases.
IAM, CI/CD, and DevSecOps tools weren't built for AI. They can't classify risk, map accountability, or enforce governance gates before a model reaches production.
Your compliance frameworks cover infrastructure and data — but not AI behavior. Who validates guardrails? Who checks PII handling in LLM outputs? Violations cost $50K–$500K per incident.
When an AI system causes harm, who's accountable? Without explicit accountability mapping across the lifecycle, responsibility falls through the cracks.
How many AI systems are running across your org? What's their risk tier? Which ones have accountability gaps? Department heads have no unified governance view.
Every AI system passes through a structured pipeline before reaching production. No shortcuts, no exceptions.
Define accountability. Map who owns what across 8 lifecycle phases.
Classify risk. OECD dimensions, data sensitivity, impact assessment.
Validate compliance. Verify code. Assure capabilities. Score 0–100.
Final checkpoint. Blocks production if any step is incomplete.
Production deployments require passing compliance, approved verification, complete assurance with gaps addressed, and a clear safety gate. Each spec version progresses independently — no shortcuts.
Two products working together: a web-based Governance Studio for your team, and a CLI that integrates into your CI/CD pipeline.
Every AI system gets a quantifiable governance score (0–100) across 7 categories before it can deploy. Guardrails, data access controls, escalation rules, PII detection, behavioral tests, policy enforcement, and RAG safety — all validated automatically.
Four-dimension risk assessment: Context, Data, Human Oversight, Autonomy. Sets governance thresholds proportional to actual stakes.
Map Causal, Moral, Legal, and Remedial responsibility to specific people across 8 lifecycle phases. Gap detection ensures nothing is missed.
AST-based code analysis discovers actual AI capabilities, derives required controls, and performs gap analysis. Scores can't be gamed by writing better YAML.
Final deployment checkpoint. Aggregates compliance, verification, and assurance results. Blocks production if ANY issue exists. Use in CI/CD with exit codes.
Org-wide command center. Risk heatmap, compliance posture, accountability status, safety gate results, and 30-day trends — every AI system in one view. Built for AI Department Heads and CISOs.
RBAC with 5 built-in roles + unlimited custom roles. 25 granular permissions. Multi-approver workflows. Immutable audit trail with cryptographic signatures. SSO/SAML integration.
The aigov CLI validates specs, scores compliance, verifies code, runs assurance, and gates deployments — all from your terminal or CI/CD pipeline.
Every industry deploying AI systems faces unique compliance requirements. AI Gov Platform has you covered.
Patient triage, clinical documentation, drug interaction systems
Fraud detection, customer service, risk assessment systems
Claims processing, underwriting, fraud detection systems
Drug discovery, clinical trial, regulatory submission systems
Compliance scoring categories
Lifecycle phases tracked
Granular RBAC permissions
Immutable audit coverage
Get a personalized walkthrough of the platform. See how AI Gov Platform fits your compliance requirements, team structure, and deployment workflow.
Our team will show you how the governance pipeline works for your specific industry and compliance needs.
Personalized demo
Response within 24h
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