Why must governance live outside the model?

If the agent that wants to act also grades whether it's safe, you still have vibes with nicer formatting. AgentGovernance's policy engine is deterministic and independent from the agent runtime.

Agent Execution Governance

The policy engine between your AI agents and the real world.

Q: What is AgentGovernance?

AI agents are starting to send emails, move money, and change records. AgentGovernance sits outside the model and decides — on every action — whether it's allowed, demands evidence and approval first, and signs an immutable receipt.

Your agents are starting to send emails, move money, and change records. AgentGovernance sits outside the model and decides — on every action — whether it's allowed, demands evidence and approval first, and signs an immutable receipt.

Try the interactive demo

agenttrust.dev/demo · 90slive engine

The demo runs the real engine — move the discount slider and it re-decides live.

The model proposes. The governance layer decides.

No external action without evidence.

Missing evidence is a hard failure.

Approvals are independent from reasoning.

The problem

Agents do whatever they're told. A prompt is not a permission.

An agent reads a stale record and emails the wrong contact. A prompt says “offer 25% off” when policy allows ten. The instruction the agent acted on was never authorization — and there was no approval step and no audit trail. Just vibes and hope.

You can't fix this with a better prompt or a smarter self-check. The thing that decides whether an action is safe must not be the thing that wants to act.

Without governance

agent.sendEmail(contact, “25% off”) → sent.
no identity · no policy check · no receipt · no way to prove what happened

With AgentGovernance

propose → evaluate(identity, policy, evidence) → require approval → signed receipt.
25% > 10% authority · stale-data guard · replayable proof

How it works

Propose. Decide. Prove.

Propose

Your agent submits a structured action request instead of calling the tool directly.

Decide

The engine checks identity, capability, policy, and evidence — deterministically, outside the model.

Prove

Allowed, approved, or blocked — every outcome is a signed, replayable receipt.

What it enforces

Identity, permission, approval, and proof — on every action.

External policy engine

Decisions live outside the LLM. The agent that wants to act never grades its own safety.

Capability contracts

What an agent may do is a declared, enforced contract — not a sentence in a prompt.

Evidence-backed receipts

Every action carries proof before it runs: source, freshness, target, diff, cost, and the permitting rule.

Independent approvals

Risky actions stop for a human. Anything over delegated authority never executes silently.

Source-of-truth freshness

No action on stale data. The record must be synced within your window — or it's blocked.

Blast-radius limits

Cap spend, rate, and reach per run. One bad loop can't do unbounded damage.

FAQ

Questions, answered.

Govern your agents before they touch production.

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