Every AI agent is a non-human identity. Each one carries a scoped credential, a token budget, and an accountable owner. When an agent needs to act beyond its scope, it stops and asks. The operator decides.
A working NHI governance surface for AI agent fleets. Six agents run as discoverable, classified, owned machine identities with scoped credentials. New credentials run an intake-and-approval workflow. Escalations route to a human. Rotation and decommissioning are in the same trail.
Sr. NHI Governance Engineer · AI / Agent Engineer · Identity Platform Engineer · Agentic AI Lead
Discovery, classification, scope check, intake, approval, credential issued, action taken, credential decommissioned.
Recorded against the live backend. The same experience is playable in the browser — open the interactive demo →
Every action is scoped, metered, and logged. Privilege escalation surfaces as a permission check failing inside the agent loop — not a hardcoded pause. Governance is enforced where the credential is used.
Each agent has a standing scope, a credential type (service account, API key, or short-lived token), and an accountable owner. Discovery, classification, and lifecycle state are visible in the surface.
Remediation needs to revoke a compromised credential. Its standing scope doesn't allow it. The system routes an intake request, attaches the assessment, and waits for the operator. New agent credentials use the same workflow.
The pause isn’t hardcoded — it’s a permission check failing inside the agent loop. What happens after approval is logged the same way:
Nine events · one credential · ~16 minutes. Every line is the system's own record — not commentary. Approval, action, expiry, and the receipt are all in the same trail, so an access review sees the whole chain of custody in one query.
The backend emits a structured event stream of identities, scopes, credentials, and approvals. The control room renders against it — real-time posture visibility with no interface coupling to any one agent.