Use case

How do you enforce governance on AI agents in production?

You enforce AI agent governance by checking every action against policy before it runs. Daena does this with a 10-stage pipeline and a four-tier risk policy that escalates from logging to human approval to a hard block, with an immutable audit trail for every action.

10-stage pipeline
Four-tier risk policy
Immutable audit log
Daena v3.7 in production

The governance problem

An autonomous agent that can call tools, move money, or change production data is only as safe as the controls around it. The hard questions are operational: who authorized this action, what was it allowed to do, and can you reconstruct the decision afterward. Governance answers those before the action runs.

How Daena enforces it

Every action passes the 10-stage pipeline — SecurityGate through AuditLog — and is classified into a four-tier risk policy. Routine actions are logged, medium-risk notify, high-risk require human approval, and critical actions are blocked. The policy is applied identically regardless of which of the 9 LLM runtimes generated the action.

What you get

A replayable audit trail for compliance and incident forensics, human approval exactly where risk warrants it, and consistent enforcement across teams and models. KYA Mission Control extends this to agent identity — verifying who owns an agent and what it may do — at kya.mas-ai.co.

Frequently asked questions

How do you govern an AI agent before it acts?

Intercept the action and evaluate it against policy before any tool call or side effect. Daena routes every action through SecurityGate, InputValidator, and a GovernanceEngine, then classifies it into a four-tier risk policy before it is allowed to run.

What audit trail should an AI agent create?

A tamper-evident record of each action: what was attempted, which policy tier applied, whether a human approved it, and the outcome. Daena writes this to an immutable AuditLog as the final pipeline stage, enabling compliance review and incident forensics.

When should a human approve an AI agent action?

For high-risk actions. Daena’s four-tier policy runs routine actions automatically (logged), notifies on medium risk, requires human approval (founder-approval gates) on high risk, and blocks critical actions — so humans review only what truly needs it.

Does governance slow agents down?

It adds a policy check, not a bottleneck. Routine actions pass through and are logged with no human in the loop; only higher-risk tiers pause for approval, so the few sensitive actions get oversight while the rest run.

Which industries need AI agent governance most?

Regulated and high-stakes ones — finance, healthcare, legal, and security — where auditability, approvals, and reproducibility are required. Daena was built governance-first for exactly these settings.