Research-grounded. Built for regulated AI at enterprise scale.
Uninformed decisions
Approvals happen without a consistent risk view, leading to reversals, rework, and slow time to launch.
Inconsistent testing
Different metrics and thresholds produce conflicting results, blocking reliable go/no-go calls.
Cross-team misalignment
Technical findings are hard to translate into legal or risk language, slowing reviews and decisions.
Regulatory uncertainty
Controls and evidence lag behind changing requirements, increasing exposure to audits and penalties.
Evidence-based decisions
A single risk view ties metrics, tests, and approvals to each system.
Standardized testing
Shared metrics and thresholds make results comparable and repeatable.
Aligned technical and risk teams
Technical evidence maps to policy language for faster review.
Regulatory clarity
Controls and documentation stay current for audits and AI Act compliance.
Scattered AI assets → one governed register.
Unknown risk → prioritized action.
Ad-hoc evidence → instant reports.
The Governance Loop
Registry
Capture every AI system and owner in one catalog.
Metrics & Techniques
Define and automate tests and mitigation steps.
Assess
Test and score risk to identify what needs attention.
Mitigate
Track fixes by method, stage, and status.
Comply
Link regulatory and internal policies to systems to assure compliance.
Audit
Export evidence-ready reports in minutes.
Governance you can prove
Centralize every AI system with ownership, value, and EU AI Act context in a single operational view.
Move from ad-hoc evidence to continuous governance with traceable metrics, mitigation, and compliance status.
Feature pillars
Single catalog with owners, value, EU AI Act category, and risk.
Define quantifiable metrics per risk with acceptable thresholds.
Testing and mitigation techniques to automate workflows.
Trend risk, detect attention items, and track status.
Policy packs, actionable controls, and evidence generation.
Move models into production faster with fewer surprises. Get clarity on model risk, performance, and lineage so teams can ship with confidence.
Turn technical evidence into audit-ready outputs. Align systems to policy requirements and maintain oversight without slowing innovation.
See how your teams can govern AI and accelerate delivery.