AI GOVERNANCE
Govern every AI system, end to end.
Discover the AI you are running, inventory it, classify and assess the risk, monitor it in production, and prove your maturity. One governed domain, aligned to the EU AI Act, ISO 42001 and NIST AI RMF.
Built For
"AI Governance is the end-to-end governance of every AI system, model and agent your organisation runs, from discovery and inventory through classification, assessment, approval, monitoring and decommissioning."
WHY IT MATTERS
AI governance that stops at a policy is not governance.
Regulators expect evidence for each system: what it is, how it was assessed, who approved it, and how it is monitored. Most organisations cannot even list the AI already running inside the business.
Framework coverage
ONE DOMAIN, FOUR MOVES
Discover, inventory, govern, prove.
Find the AI nobody told you about.
Shadow AI enters through SaaS features and team-level adoption faster than any register is updated. Shadow AI Discovery surfaces unsanctioned AI and AI-enabled features across your estate, so what you govern matches what is actually running.
Unsanctioned AI and AI features, surfaced
New finds risk-flagged for review
Continuous, not a one-off survey
Every AI system on one register.
The AI Register and Catalogue is the authoritative inventory of your AI systems, models and agents, with owner, purpose, risk tier and framework coverage on each. It is the baseline every other AI control reads from.
Owner and risk tier on every entry
Framework coverage per system
The single source other controls read
Classify, assess, approve, monitor.
AI Governance runs each system through its lifecycle: risk classification, impact assessment where required, approval with separation of duties, monitoring in production, and decommissioning. AI proposes, accountable people confirm.
Risk classification, human-confirmed
Fundamental rights impact assessment
Approval gates with separation of duties
Know where your AI governance stands.
AI Maturity Assessment benchmarks your AI governance against recognised models such as NAII, NIST AI RMF and ISO 42001, producing an evidenced score and a clear path to the next level. A number the board can act on.
Benchmarked against recognised models
Each level backed by evidence
A clear path to the next level
EU AI ACT COMPLIANCE
The high-risk obligations, evidenced.
For systems that fall in scope, the EU AI Act sets out what good looks like. The platform turns each obligation into evidence you can show, per system, mapped to the article.
Risk management
A documented risk management system across the lifecycle.
Data governance
Training and input data quality, evidenced.
Technical documentation
Assembled per system and kept current.
Transparency
Instructions for use and disclosure on the record.
Human oversight
Oversight measures defined and evidenced.
Accuracy and robustness
Performance monitored against thresholds.
Fundamental rights impact
A FRIA prepared where the Act requires it.
HOW IT CONNECTS
AI risk flows to Enterprise Risk Management. Framework definitions come from Regulatory Intelligence. Your whole AI posture surfaces in the Governance Twin.
See the Governance Twin