governance · risk · compliance
GRC for AI agents
A GRC program for an agent estate answers three questions on a loop: what are the rules, where is the exposure, and can you prove both to someone outside the room. VisIQ runs the loop on runtime fact rather than self-assessment: policies govern live decisions, exposure is scored from the estate discovery actually found, and every decision leaves a signed receipt.
Governance is a rule that fires, not a document
Most AI governance programs are documents: an acceptable-use policy, a review board, a register of approved models. None of that touches an agent at the moment it acts. The governance half of GRC only counts when the rule is on the execution path, deciding each action before its side effect lands.
VisIQ policies are written once against one canonical event schema and evaluated in the live lane. The outcome set is small and complete: permit, deny, approval required, redact, escalate, mask. A policy nobody can enforce is a wish; these fire.
Risk is measured on the estate you actually have
The risk half fails when it starts from a self-reported inventory, because most of an agent estate arrives unregistered. Discovery finds the fleet, including the agents nobody onboarded, and posture scoring ranks what it found: credentials broader than the job, reach into stores the work never requires, agents running under no policy at all.
Every agent carries a business function and a human-assigned trust tier, so the ranking is not generic: a wide grant on a low-trust agent in a sensitive function rises to the top, and the remediation is a scoped rule rather than a meeting.
Compliance is a receipt, not a recollection
The compliance half is the proof: when an auditor asks who approved an action, under which policy version, and what the agent was allowed to see, the answer has to be a record, not a memory. VisIQ signs a receipt for every decision it makes: the event, the rule that matched, the outcome, and the human in the loop when one was required.
That trail is what your team maps onto the framework of record, whether that is NIST AI RMF, the EU AI Act, or ISO 42001. The framework names the control; the receipt is the evidence the control operated.
The loop, closed
GRC for agents is one loop run continuously: discovery keeps the inventory true, posture keeps the risk ranking current, policy keeps the rules firing, and receipts keep the evidence flowing. Remove any stage and the others degrade into paperwork.
Start where your gap is widest. If you cannot name the estate, start with discovery. If you can name it but not rank it, start with posture. If you can rank it but not stop anything, the rules and the receipts are waiting.