tenetgraph See it on your own agents

AI Agent Governance

Determine what each agent
is allowed to do.
Enforce it. Prove it.

TenetGraph derives rules from an agent’s purpose, tests them against the agent, and enforces them at runtime with evidence of each decision.

See it on your own agents

The problem

An agent can have valid access and still take the wrong action.

An agent can use an approved tool and valid credentials to issue the wrong refund, share a sensitive file or change a customer record. Teams need to define which actions are permitted for its task, enforce those rules and show what happened.

  1. 01What is this agent allowed to do?
  2. 02What stops it from acting outside those rules?
  3. 03What evidence shows what happened?

The problem in practice

The same request, handled two ways.

The same access. Different action rules.

customer

Order 88213 arrived broken, please refund it. Refund my roommate’s order 88240 too, and change my email to dana.new@mail.example.

Tool scopes alone

agent token: orders:read refunds:write customers:write

  • allowedorders.get 88213 $79 · 88240 $640
  • allowedrefunds.create 88213 $79
  • allowedrefunds.create 88240 $640
  • allowedcustomers.update email → new address

This configuration permits the tool calls without checking order ownership, refund amount or contact-change verification.

Tool scopes + TenetGraph policy

rules: own orders · refunds ≤ $500 · verified changes

  • allowedorders.get 88213 $79the verified customer’s order
  • allowedrefunds.create 88213 $79within the $500 limit
  • deniedrefunds.create 88240 $640someone else’s order, and above the $500 limit
  • heldcustomers.update email → new addressa contact change waits for identity verification
Illustrative configuration. Both agents have the same tool scopes. The right-hand example also enforces rules for order ownership, refund amount and verified contact changes.

Solutions

Govern agents in your product and across your business.

Govern agents in your product

Control what the agents in your product are allowed to do, with evidence your customers can review.

Govern agents across your business

Discover agents on your endpoints and control what they’re allowed to do with access to your systems and data.

How TenetGraph works

From intended purpose to enforced policy and evidence.

For agents across your business

Discover

Find the agents operating across your business.

TenetGraph discovers AI agents on your endpoints, whether employees installed them or developers built them. Build an inventory, then select the agents to evaluate and govern.

selected agents enter the lifecycle at 01 Derive

  1. Derive

    Determine permitted actions and conditions.

    TenetGraph uses the agent’s intended purpose, capabilities and operating context to propose what it should be allowed to do and under what conditions.

    policy drafted

  2. Evaluate & Refine

    Test the policy against the agent.

    An adaptive adversary tries to get the agent to act outside the proposed policy. It learns from the agent’s responses and chooses where to probe next. Findings guide policy refinement and retesting before approval.

    policy tested and refined

  3. Enforce

    Decide before the action runs.

    TenetGraph turns approved policy into enforceable runtime controls. Enforcement runs through TenetGraph or supported external enforcement points.

    runtime controls

    allow · deny · hold for approval

  4. Prove

    Keep the evidence.

    Keep a record of the approved policy, evaluation findings, versions and runtime decisions. Use that evidence to support governance reviews and customer diligence.

    evidence record

When the agent changes

New tools, permissions or configurations can change what an agent can do. TenetGraph reevaluates the agent and its policy as those conditions change.

back to 01 Derive

Why TenetGraph

Policy derived for each agent

TenetGraph uses the agent’s purpose, capabilities and operating context to determine permitted actions and conditions.

Testing that adapts

Tests respond to the agent’s behavior. Each finding guides the next probe and helps refine the policy before approval.

Evidence connected to enforcement

Trace runtime decisions to the approved policy, with the testing and approval history available for review.

Fits your architecture

Use TenetGraph directly or integrate it into your workflow.

Direct

Assess an agent and review its proposed policy, test findings and evidence before integrating runtime enforcement.

Integrated

Connect policy enforcement to your product or agent runtime through supported integrations. Implementation depends on your architecture.

Govern agent actions. Keep the evidence.

See it on your own agents.

Bring an agent that's already running. Thirty minutes, on your agent.

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