Governance, risk, and compliance — provable.
Governance, risk, and compliance on the governed platform, end to end: AI governance, data privacy, and third-party risk, each carried through to provable, audit-ready evidence. They run on one shared inventory, so exposure that spans AI, privacy, and vendors rolls up into a single risk view.
Assessments, high-risk systems, and governance status on one live dashboard — the whole AI risk posture at a glance.
Take every AI system, vendor, and data flow from registration to audit-ready evidence — on a record that verifies itself.
The actual Risk & Compliance workspace, screen by screen.
Not mockups — the real product surfaces, every agent, record, and governed action on one system. Click any frame to see it full size.
Every AI system you run, in one inventory
AI does the routine work under the limits you set — but you cannot govern what you cannot see, so this registry inventories every AI system in use and scores how risky each one is against the frameworks regulators use.
Each system carries its usage context, its risk classification, and its assessment status, so you can answer “which AI do we run, and how risky is each” before anyone asks.
Machine-readable policy that enforces as the AI runs
The limits you set are written as machine-executable policy that enforces in the moment an agent acts — screening for prohibited uses, redacting personal data, gating risky deployments — and one rule, “require human review for high-risk decisions,” is what makes anything consequential stop for a person.
Dry-run a new rule against sample inputs to see exactly what it would block or allow before it goes live, so a control never surprises you in production.
Where consequential AI actions wait for a human
When an action is high-risk, low-confidence, or simply novel, the agent does not just proceed — it stops and routes to this queue, where a named reviewer approves, modifies, or rejects it before anything happens, each request on its own clock.
Every escalation shows the agent’s recommendation and the reason it paused, so the human decides with full context — and the resolution is written back against the request.
Every AI agent bound to a risk level and real limits
Each agent doing the routine work runs under governance, not on its own recognizance — tied to a risk level, a state you control, and the policies that apply to it, so autonomy always maps to limits your team already understands.
Pause a high-risk agent, keep watch on a critical one, or register a new one with its guardrails attached from the very first run.
Your vendors and their AI, watched continuously
Governance does not stop at your own AI — the same record-keeping discipline carries to third parties, tiering each vendor by criticality, scoring inherent and residual risk, and surfacing the findings that need attention before a supplier becomes your exposure.
Criticality tiers, inherent-versus-residual scoring, and open findings roll up to one view, so third-party exposure is managed end to end instead of once a year.
Every decision sealed into a tamper-evident record
Every governance action above — each policy block, each oversight decision, each approval — is immutably recorded, and governance events are sealed into a SHA-256 hash chain where altering a single entry breaks it and is immediately detectable.
Filter by entity, action, user, or date and export the exact slice an auditor asks for — the complete, verifiable history of who did what, when, and from where.
Every governance decision is written to a tamper-evident record: alter one entry and the chain breaks.
For risk, compliance, privacy, and audit teams. It runs on the same governed platform as everything else — one permission model, one verifiable record, and the same agents acting under the limits you set. Part of one governed platform: start with Risk & Compliance and add the rest when you’re ready, with nothing to re-integrate or re-secure.
See Risk & Compliance on your own work.
Bring a real example and we’ll walk it through Risk & Compliance — under the same controls you’d run in production.