Platform governance teams answering which agents can reach which tools and resources.
Whether Endram provides the runtime control and evidence needed for ai agent capability inventory.
The control gap
Tool catalogs show what an integration exposes, while policy documents show intended rules. Neither alone reveals the combination of agent identity, delegated task, actual resource use, and exceptional approval.
A capability inventory differs from a list of connected apps. One integration can expose dozens of actions, each with different resources and side effects. The inventory should answer which verified or asserted agent attempted each canonical tool, which resource selector was resolved, which environment was involved, and whether policy allowed, denied, or escalated it.
Use inventory during onboarding and incident response. In shadow mode it reveals the action vocabulary needed for policy. In enforcement it identifies newly observed resources, denied unknown tools, inactive principals, and stale access. Keep discovery separate from authorization: a server advertising a tool does not grant an agent the right to invoke it, and observed use does not automatically publish permission.
What good looks like
A runtime inventory connects observed capabilities with policy and evidence so stale, unused, or unexpectedly broad reach can be reviewed.
- Agent-to-tool mapping
- Resource observations
- Identity verification state
- Policy and approval context
A production workflow
- Capture authorization calls
- Normalize agents and tools
- Aggregate resource reach
- Compare observations with policy
Evidence to require
- Last-seen capability
- Allowed and denied attempts
- Verified delegator and task
- Rule responsible for access
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 capability inventory?
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.