Role-Based Access Control applied to AI agent management — different team members get different permissions for viewing, configuring, and approving agent actions.
RBAC means not everyone on your team can do everything. An admin can configure agents and approve actions. An operator can monitor and trigger actions. An auditor can view logs but not change anything.
Applied to AI agents, RBAC ensures that only authorized team members can modify agent behavior, approve risky actions, or access sensitive audit data.
As teams grow, you need granular access control. An intern should not be able to modify production agent policies. RBAC prevents unauthorized changes and provides accountability for who did what.
Clawctl Business plans include RBAC with admin, operator, and auditor roles. Team plans support 3 team members. Business plans support granular role assignment.
Try Clawctl — 60 Second DeployAdmin (full access), Operator (monitor + trigger), Auditor (view logs only). Enterprise plans support custom roles.
Business plans ($999/mo) and above include full RBAC.
Enterprise plans support custom role definitions.
Policy Engine
A rule system that defines what an AI agent can and cannot do, with versioning, rollback, and enforcement.
Audit Trail
A chronological record of every action an AI agent takes, providing accountability, compliance evidence, and forensic capability.
Tenant Isolation
The complete separation of resources, data, and credentials between different customers (tenants) on a shared platform.
SIEM Export
The ability to export AI agent audit logs to a Security Information and Event Management system for centralized security monitoring.