A rule system that defines what an AI agent can and cannot do, with versioning, rollback, and enforcement.
The policy engine is the brain of agent governance. It stores rules about permitted actions, blocked operations, approval requirements, and behavioral constraints. Policies are versioned — you can roll back to a previous policy if a change causes issues.
Policies cover tool access, network permissions, file system access, and behavioral rules. The engine evaluates every agent action against the active policy before allowing execution.
As agent deployments grow, managing security through individual configurations becomes unmanageable. A policy engine centralizes governance, ensures consistency, and provides an audit trail of policy changes.
Clawctl includes a policy engine with versioning and rollback. Define rules through the dashboard or CLI. Changes are tracked and auditable. Roll back instantly if a policy change causes issues.
Try Clawctl — 60 Second DeployYes. Every policy change creates a new version. Roll back to any previous version instantly.
Tool access, network permissions, blocked actions, approval requirements, and behavioral constraints.
Yes. Assign policies per agent or use a default policy with per-agent overrides.
AI Guardrails
Safety boundaries that constrain what an AI agent can and cannot do, preventing harmful or unintended actions.
Approval Workflow
A process where risky agent actions are paused and routed to a human for review before execution.
RBAC for AI Agents
Role-Based Access Control applied to AI agent management — different team members get different permissions for viewing, configuring, and approving agent actions.
SIEM Export
The ability to export AI agent audit logs to a Security Information and Event Management system for centralized security monitoring.