AI agent governance · action-level authority

AI agent governance that gives agents authority one action at a time.

Createting evaluates what an agent is trying to do, which resource it targets, what side effect it creates and whether that exact action can proceed automatically, requires review or must be denied.

Configured product example. Policy behavior depends on the action contract and deployment context; this page does not imply a certification or universal security guarantee.

ActionPolicyGateCustomer Operations Agent
ASK

Action descriptor

Actionbilling.create_credit
ResourceAccount ACME-1842
EffectExternal financial write
RiskMaterial
ConditionCredit ≤ €500 · outage evidence
Evidence trailPolicy evaluation recorded · execution blocked until approval

Direct answer

AI agent governance controls authority at the point of action.

A useful agent can read data, call tools, browse, delegate and change external systems. Those actions do not carry the same operational risk, so a single “autonomous / not autonomous” switch is too coarse.

Createting evaluates the requested action and its context before the side effect occurs. The result can be ALLOW, ASK or DENY, with evidence that explains why.

Authority contract

The policy decision follows the action, resource and effect.

01

Action type

Tool, browser, computer, external API, memory write, subagent, artifact or another governed execution category.

02

Target and side effect

Which resource is affected, whether data leaves the system and whether the request creates an external change.

03

Conditions and risk

Workflow-specific limits such as amount, account scope, evidence requirement, sensitivity, target or deployment stage.

04

Decision and evidence

ALLOW executes, ASK pauses for a bound human approval, and DENY prevents the external effect while retaining decision evidence.

Approval integrity

A reviewer approves the exact requested action—not a vague future permission.

01
Pause before effect

The consequential action waits before the external system is changed.

02
Bind the approval

Action, arguments, target and expected effect are fingerprinted so the approved request cannot silently drift.

03
Resume with evidence

After approval, the agent can resume the same governed execution path and retain the decision in its operating evidence.

Current boundary

Governance mechanisms are not the same thing as a compliance certification.

Tenant-scoped runtime context, resource boundaries, action policies, approvals, sandbox controls and execution evidence can contribute to a secure deployment, but the actual security posture still depends on infrastructure, secrets, identity configuration, provider choices, workflow design and environment validation. Createting should not claim SOC 2, ISO, GDPR compliance, zero trust or universal production readiness without current evidence.

FAQ

Questions before an agent receives operational authority.

What is the difference between autonomy and authority?

Autonomy describes how independently an agent works. Authority describes what a particular action is permitted to change. A highly autonomous agent can still operate under narrow action authority.

What happens when an action requires review?

The external effect pauses, the requested action is presented with its arguments and target, and an authorized reviewer can approve or reject that exact request.

Can policies differ by workflow?

Yes. Limits and conditions should reflect the actual workflow, resource, risk and deployment context rather than a single platform-wide permission level.

Does governance guarantee a secure deployment?

No. Governance controls are one layer. Deployment security also depends on identity, secrets, infrastructure, providers, tenant boundaries and environment-specific validation.

Start with one consequential action

Define who or what is allowed to change the outside world.

Map the workflow, the action surface, the failure cost and the approval boundary before expanding agent autonomy.