Clinical and patient records updated by an agent acting through a service account.
Independent governance for agentic AI
Move AI agents from pilot to governed production.
Security, risk and compliance block agents that can act. GovernorAI finds the agents nobody registered, decides each consequential action against your policy — allow, deny, or hold for a human — and writes a record your auditors can verify. You keep building: we don’t build, host or take over your agents.
Read-only discovery Policy at the model call and the action Tamper-evident audit ledger Fails closed by contract
Governance lifecycle · sample environment
org_sample_01 04 / ENFORCE Refund held for approval
erp.process_payment · $12,400 · rule 3 → require_approval
target system: unchangedEvidence stream connected
illustrative valuesModels decide. Agents act.
GovernorAI governs both.
THE PLATFORM
One lifecycle, seven surfaces.
Each stage is a place you can start. Discovery is read-only and needs no enforcement decision; everything after it is a choice you make with evidence rather than a leap.
01 · Discover
Discovery & Shadow AI
Inventory the agents, tools, MCP connections and SaaS copilots nobody registered — read-only, from sources you already run.
See discovery → 02 · AssureAssurance
Evaluate an immutable agent snapshot against preregistered bars before it reaches production. Six domains, with measurability computed per deployment.
See assurance → 03 · GovernPolicy & Governance
Native, CEL and Rego — or point at the OPA server you already operate and write no policy here at all.
See policy → 04 · EnforceRuntime Enforcement
Allow, deny, approve, redact, mask or constrain at the action boundary — and only the outcomes an enforcement point can genuinely carry out.
See enforcement → 04 · EnforceInference & Model Governance
Which models may be called, what may be sent, and what may come back — governed without sitting in your token path.
See inference → 05 · ProveEvidence & Compliance
A hash-chained, tamper-evident record of governance actions, mapped to the controls an assessor will ask about.
See evidence → Across the loopDecision Observability
Policy verdicts, approvals, drift and fleet health — the record of what a control did and why.
See observability → Scope boundary You build the agent. GovernorAI independently governs what it is allowed to do.
We do not build your agents, host them, or sit in the availability path of every token. That independence is why the evidence stands up when a security or compliance team examines it.
THE CONSEQUENCE PROBLEM
Agents are no longer just answering questions.
A wrong answer is a support ticket. A wrong action is an entry in a system of record — made under an identity nobody reviewed, at a speed no approval queue was designed to absorb.
Refunds, payouts and adjustments executed without a human in the path.
Infrastructure, entitlements and configuration altered by a process, not a person.
The gap When an agent can act, a policy document and a log after the fact are not enough.
ADOPTION
Start read-only. Expand control where consequence is highest.
Sequenced by risk, not by upsell. Nothing enforces until you decide where enforcement belongs — and a policy can run in shadow against production traffic before it is allowed to block anything.
Discover unknown AI activity
A low-friction, read-only inventory for security teams. Nothing is intercepted and nothing changes how your agents run.
Read-onlyEstablish evidence
Align a governed action trail to what security and compliance review actually asks for, before any enforcement decision is made.
Evidence firstEnforce at the action boundary
Add policy, approvals, data controls and stop controls where the integration supports them — starting with the workflow that carries the most consequence.
Where supportedWHO THIS IS FOR
Designed for the teams accountable when AI takes action.
Three buyers, one governed action trail. Each sees the same decision from the side they answer for.
Security
Per-call authorization, injection defences, data controls and stop controls — at supported enforcement points.
Security → GRCEvidence chains and control mapping for governed actions, in the form a reviewer actually asks for.
GRC → Platform & AI EngineeringA policy and evidence layer around the agents, models, frameworks and tools you already run.
Platform & AI → How to read this site
Every capability page states what it does and what it does not. Outcomes are limited to what each enforcement point genuinely supports, assurance domains that cannot be measured in your environment report not_assessed rather than a pass, and mapping evidence to controls is not certification. Where a boundary exists, we print it rather than omit it.
DESIGN PARTNER PROGRAM
Make the agents you already run governable.
For security, compliance and platform leaders deploying consequential agentic AI.