IAM and platform teams that need agents to act as accountable principals instead of caller-supplied names.
Whether Endram provides the runtime control and evidence needed for ai agent identity platform.
The control gap
A display name in an API payload is not an identity. Without cryptographic provenance, any caller can impersonate an approved agent and satisfy a name-based rule.
Evaluate an identity platform by attempting impersonation, not only successful enrollment. Send the same approved agent name without its principal secret, reuse an expired delegation, change the environment during token exchange, and alter the task after issuance. A verified-only rule must deny every variant. The resulting receipt should state that the caller was asserted or invalid instead of silently treating a display field as proof.
The shipped native flow is deliberately self-contained: an administrator registers a stable principal and receives its secret once; a logged-in human issues a signed delegation; the runtime exchanges both for a fifteen-minute identity token. This establishes the product behavior without making an enterprise identity provider mandatory. OIDC workload federation is a future adapter and is not represented as already available.
What good looks like
Stable agent principals, one-time secrets, signed human delegations, and short-lived identity tokens give every authorization decision a verifiable actor chain.
- Hashed principal secrets
- Signed delegation with purpose and expiry
- Verified identity policy conditions
- Identity provenance in receipts
A production workflow
- Register the agent principal
- Create a task-bound human delegation
- Mint a short-lived runtime token
- Evaluate verified claims on each action
Evidence to require
- Principal and instance identifiers
- Delegator, task, run, and purpose
- Verification state and expiry
- Decision and execution linkage
Buyer checklist
- Can the product enforce a decision before the external tool executes?
- Can policy distinguish the agent, delegated user, tool, resource, and environment?
- Can reviewers see the exact requested action and approve it without broadening future access?
- Does every allow, deny, and approval retain the policy version and reason?
Practical answers
Common implementation questions
What does Endram control for ai agent identity platform?
Endram evaluates the concrete tool call at runtime. It can allow, deny, or pause the call for approval using agent identity, delegated authority, action, resource, environment, and request context.
Does Endram replace the tool's own IAM?
No. Keep native IAM and OAuth scopes as the outer boundary. Endram adds a decision layer for the actions an agent attempts inside those credentials.
Can teams evaluate policies before enforcing them?
Yes. Shadow mode records the decision Endram would make without interrupting the call, so teams can measure impact before switching a policy to enforcement.