AI AND MODEL GOVERNANCE FOR REGULATED INDUSTRIESYour GRC System
Can Record a Control.
It Has Never Stopped
an Agent.
Auditrol connects policies, controls, data, and owners into one execution layer, so agents reach production and models stay defensible.
EXECUTION LOOPRisk is not managed until these three are true.
One context layer
Across policies, controls, models, agents, data, and the people who own them. Metadata pulled live from SAS, your data warehouse, and the applications your controls execute against.
Controls that run
Against live data on every execution. When an agent crosses a policy boundary, it stops. The owner hears about it before you do.
Evidence syncs back
Written back into ServiceNow and the other tools your control owners already work in. Nobody logs into a separate risk tool to attest. The exam package assembles itself.
DOMAINSStart with one risk domain.
TRUST MODELBuilt with regulated industry standards, architecture, and security.
Connecting humans and machines.
Human review is a gate, not a setting
No AI-generated finding becomes evidence without a named person approving it. The approval is part of the audit record, with the citation and the confidence score attached.
Your data stays yours
Single-tenant isolation. Not pooled with another institution's, and not used to train shared models. SOC 2 Type II.
Answers carry their sources
Every answer returns a citation and a confidence score, so a reviewer can check the source rather than trust the summary.
Every step is audit logged
What the system read, what it inferred, what it acted on, and who approved it, exportable for an examiner or an internal audit request.
NEXT STEPPoint it at a system you already own.
Auditrol runs a live control against your own data, in your own stack, no migration required to evaluate it.