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With Proofable, every finished agent job carries a signed receipt. The next agent checks the receipt instead of paying to redo the job.

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What it saves you

750 times faster to check a Proofable receipt than to redo the job: redoing it took 2.79 seconds, checking the receipt took 3.7 milliseconds. 750 times faster to check a Proofable receipt than to redo the job: redoing it took 2.79 seconds, checking the receipt took 3.7 milliseconds. 750 times faster to check a Proofable receipt than to redo the job: redoing it took 2.79 seconds, checking the receipt took 3.7 milliseconds. 750 times faster to check a Proofable receipt than to redo the job: redoing it took 2.79 seconds, checking the receipt took 3.7 milliseconds. One finished agent job on the live service, timed October 20, 2026. Redoing it also used 2,426 AI tokens; checking the receipt used none.

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What it stops

48 of 48 agent governance scenarios for Proofable beside the agent tools teams already use: on their own they handled 13, Cursor with the ACP gateway 37, and Claude Code or Codex with ACP 43. 48 of 48 agent governance scenarios for Proofable beside the agent tools teams already use: on their own they handled 13, Cursor with the ACP gateway 37, and Claude Code or Codex with ACP 43. 48 of 48 agent governance scenarios for Proofable beside the agent tools teams already use: on their own they handled 13, Cursor with the ACP gateway 37, and Claude Code or Codex with ACP 43. 48 of 48 agent governance scenarios for Proofable beside the agent tools teams already use: on their own they handled 13, Cursor with the ACP gateway 37, and Claude Code or Codex with ACP 43. AgentGovBench is the open benchmark for agent governance: 48 scenarios such as a sub-agent reaching past its parent’s limits or one customer’s data reaching another. The agent-tool rows are the maintainers’ published results on the earlier version of the library, where Claude Code, Codex CLI and Cursor each handle 13 on their own. On the current version, run October 20, 2026 against the policy code the live service runs, Proofable handles all 48 and ACP, the maintainers’ own gateway, handles 46. 8 of 8 permission tests passed on the live service. Every action outside the agent’s permission was stopped before it ran, and the actions it was allowed to take ran. When an agent was taken over, a scoped permission refused 6 of 6 attempts to send private data out, before they ran; an all-purpose key let all 6 through. The scoped agent still finished every task and never used a tool it did not need; under the all-purpose key, 14 of 36 runs did. Self-run: 84 runs, five published attack templates, two models, a signed record for each run. Run the test on your own agent. 150 of 150 forged records caught. We changed each of our 15 real records ten ways. Every changed copy failed verification and every real record passed.

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Test it in a minute

Time a reuse on your own machine, with no account and no API key:
It reads a finished agent job by its id, verifies the signed receipt locally, and prints the time and the AI tokens used. Expect a few milliseconds and zero tokens. Pass any public record id to time that record instead. To put receipts on your own agent’s work, add Proofable to your AI tool.

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Details for reviewers

This record is a finished agent job from the live service. Producing it took 2.79 s and 2,426 AI tokens. On October 20, 2026, verifying its signature offline took 3.7 ms, the median of ten runs, with no account and no AI tokens. The command in Test it in a minute repeats the measurement.
We ran each test on the live service on October 8, 2026, with a dedicated agent under its own fixed permission. Each link opens that test’s signed record.To rerun the same eight tests on any account you control, create an access key under Profile, Account tab, Access keys, then:
The same records are part of the AAIF Identity & Trust working-group comparison at the Linux Foundation.
The eight tests produced 15 signed records. Check all of them on your machine, with no account:
This check takes the 15 real records and changes each one ten ways, such as editing the content, swapping the owner or flipping one bit of the signature. Then it verifies every copy. All 150 changed copies fail and all 15 real records pass. A check that only looks at the format would accept every changed copy.
AgentGovBench is an open library of 48 agent-governance scenarios in eight areas: audit completeness, cross-tenant isolation, delegation provenance, fail-mode discipline, identity propagation, per-user policy, rate limits and scope inheritance. Each scenario is tagged with the NIST AI RMF controls it tests. Its maintainers revised the library in October 2026 so that nothing passes on a technicality.We ran the current library (commit 479c5f0) against the exact policy code the live service runs, matched to it by hash, next to a gate that allows everything and no governance at all. The run called that code directly, so it measures the decision logic rather than the hosted service end to end. Last run: October 20, 2026.On the earlier library (commit e0ce93a) the same engine also handles 48 of 48, where the maintainers measured the agent tools teams already use:The agent-tool rows are the maintainers’ published results, run end to end against their gateway and not re-measured on the current library. The Proofable rows call the policy code directly. The scenarios and scorer are the same and the setups are not, so read the tables as a comparison of what each approach covers, not as a ranking. Proofable also handles the one scenario ACP declines: holding a sub-agent to a narrower task than its parent.
Each result maps to the published control it gives evidence for. None of these mappings is a certification or a compliance opinion.The frameworks: OWASP Top 10 for Agentic Applications 2026, the EU AI Act, the NIST AI RMF, the NIST NCCoE agent identity and authorization project and CAIP-380.
Last modified on October 20, 2026