Operate AI systems with continuous control and accountability
Calvin Risk turns AI governance from static documentation into an automated control system, powered by real testing evidence and continuous oversight.
Most AI governance is documentation that's already out of date.
Static records can't keep up with systems that change with every prompt, dataset, and model update. The gaps stay hidden until an incident or an audit exposes them.
Govern AI across its full lifecycle.
of AI applications tracked, classified, and linked to live evidence, by use case and risk tier.
Lifecycle management
Track AI applications, use cases, owners, lifecycle stages, and deployment status in one register.
Risk classification
Assess and update system risk from use case, impact, regulatory exposure, and observed behavior.
Regulatory alignment
Map governance to internal policy and audit expectations, ready for review.
Audit & documentation
Generate traceable records that connect risk assessments, test results, and decisions.
Oversight & accountability
Review, approval, escalation, and sign-off across engineering, risk, compliance, and leadership.
What governance handles, in the moment.
New high-risk systems
Classified, documented, and ready for deployment review.
Model update shipped
Re-assessed and re-evidenced before it reaches production.
Regulator requests
A complete decision trail, produced on demand.
Cross-team review
One source of truth across engineering, risk, and compliance.
From inventory to continuous oversight.
Inventory
Track systems, use cases & owners
Classification
Risk tier by impact & regulation
Evidence
Linked to real test results
Documentation
Audit-ready records, auto-generated
Oversight
Review, approval & accountability
The operated governance layer.
One system to track AI systems, classify risk, align with regulation, and maintain traceable evidence from development to production.
Continuous visibility across AI applications
Dynamic risk classification
Full traceability from test to decision
Oversight & approval trails
Regulatory alignment & audit readiness
Automated evidence generation
Policy & audit alignment
Continuous documentation updates
Testing becomes the foundation for AI governance.
Every evaluation generates evidence that feeds into risk assessment, documentation, compliance workflows, and deployment decisions.
AI behavior evaluated
Systems are tested across world scenarios.
Evidence is generated
Results become audit-ready documentation.
Risk is updated
Classifications are continuously tracked
Decisions are grounded
Oversight is based on measurable behavior.
“This type of AI testing & governance is much better than the previous manual approach.”
See how governance becomes continuous control.
Learn about why AI risk appears differently across industries, workflows, and decision systems.
Ready to assure your AI systems? Learn how your systems behave and make them trustworthy by design.
Data & analytics
Ship systems that behave reliably
Risk & compliance
Establish continuous, defensible oversight
Business leaders
Scale AI without hidden risk