Give AI agents real identities, not shared keys

Move from generic service accounts and hardcoded credentials to agent-native identity, access, and audit models built for autonomous workflows.

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Why Choose ProofMap

Issue scoped credentials per agent task

Create short-lived access that matches what the agent is allowed to do right now instead of giving it standing broad permissions.

Track auditable action chains

See which agent acted, under what delegation, and against which resource so investigations do not collapse into shared-key ambiguity.

Support agent-to-agent delegation

Model how autonomous systems pass authority safely when one agent calls another or hands off work across workflows.

Comparison

IAM challenge	Human-centric default	Agent-native identity model
Credential management	Reuse service accounts or shared API keys across many workflows.	Issue scoped, short-lived credentials aligned to one agent, task, and policy boundary.
Auditability	See that a system acted but not which autonomous actor made the decision.	Preserve the identity, delegation path, and action context for each step.
Delegation	Bolt custom logic onto human IAM systems.	Represent agent-to-agent authority transfers explicitly so trust chains remain understandable.

Frequently Asked Questions

Why can human IAM patterns fail for agents?

Agents act autonomously, operate continuously, and often call tools or other agents in chains. Shared credentials and human-centric roles do not map cleanly to that behavior.

What should teams change first?

Start by removing shared credentials for high-risk workflows and replacing them with scoped, auditable identity primitives.

How does this connect to runtime safety?

Identity is one of the main enforcement tools for runtime safety because permission scope determines what an agent can actually do when something goes wrong.

Modernize identity for autonomous systems

Give AI agents the scoped access and audit trails that human IAM models leave behind.

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