Runtime and tenant identity
Know which tenant, runtime, workspace, and owner are associated with each agent.
Governance and auditability
How can an ops team control and audit what AI agents do across the company?
Control company AI agents by assigning each runtime a clear tenant boundary, governing its policies and skills, managing access and credentials, and retaining inspectable run and usage evidence. Hermes Hub and the surrounding Bewize product layers provide named operating controls for this review; they do not justify blanket security or compliance guarantees.
The operations checklist
An audit-friendly agent program connects control points to evidence and an owner.
Policy and capability boundary
Define which skills, tools, and runtime behaviors are available.
Access and secrets
Track access state and managed credential metadata without exposing raw secrets.
Run and usage evidence
Review outcomes, token usage, schedules, and operational signals tied to the runtime.
Evidence sources
Security governance
Tenant isolation, policy APIs, managed secrets, access blocking, and redaction controls.
Learn moreHermes Hub console
Fleet state, run history, schedules, files, skills, and configuration context.
Learn moreEvaluation
Pair operational controls with evaluation evidence before widening agent capabilities.
Learn moreAI agent audit FAQ
Does an audit mean recording every model token or internal thought?
The practical scope is operational evidence such as runtime identity, access state, run history, tool activity where exposed, usage, schedules, and policy changes. Do not infer access to private model internals.
How should teams handle secrets during an audit?
Review secret metadata, scope, status, and refresh controls while keeping raw secret values out of casually copyable operator surfaces.
What is the first control to establish?
Start with a tenant and runtime inventory, then connect each agent to an owner, policy boundary, access state, and evidence record.