AI agent audit and compliance tools compared

For the team that builds and runs the agent: traces, evaluations and debugging.

Pick one of these when you are building an agent and need to see why it failed. They are built for the team that runs the agent. APIR is not a debugging or evaluation tool: no trace explorer for prompts, no evals.

For the risk, legal and compliance teams running an AI programme across many systems.

Pick one of these when you need an inventory of every AI system, risk reviews and policies mapped to the frameworks your regulator names. APIR is not a compliance platform: it runs no programme and writes no policy. A governance team can use APIR's record as evidence about one agent.

For the day an AI error costs someone money.

Pick one of these when you need cover, or a certificate a buyer recognises. Armilla's own page says "Enterprise buyers now ask AI vendors for proof of insurance." APIR is not an insurer or a broker, has no underwriting partner, and certifies no one. What it can give an underwriter or an auditor is the agent's history, checkable without trusting the vendor.

For controlling who an agent is and what it may reach.

Pick one of these to control access inside your company, or to let a website recognise an agent acting for a person. Identity says who the agent is. It does not by itself give an outsider a record of what the agent did. See APIR and Microsoft Entra Agent ID.

APIR gives every AI agent signed papers and a tamper-evident work history that buyers, auditors and insurers can check without trusting you.

What we found on 27 October 2026: on the pages we read, none of the thirteen products above described its logs as signed, hash-chained or tamper-evident, or said an outside party could check the record without access to the product. Vouched signs an agent's identity and delegations, AIUC-1 relies on an accredited auditor, and Microsoft's agent logs sit in the tenant's own Entra logs. A product can do more than its marketing pages say, so check their documentation for your case.

Other projects do sign or hash-chain an agent's record: open protocols, an open-source library, runtime features, IETF drafts, an on-chain registry and hosted services. They are not in the thirteen above because they are not audit or compliance tools; they are read on their own pages and compared in who gives AI agents a tamper-evident work history.

APIR does not trace prompts for debugging, run evals, keep an AI inventory, map policies, insure anything or certify anyone. Its log book proves what an agent reported and shows any later change to it, not that the report was complete.

They are not either-or. Most teams that need one need two.

• Your agent fails and you need to see why: an observability tool such as LangSmith, Langfuse, Arize or AgentOps.
• You run AI across a large organisation and answer to a regulator: a governance platform such as Credo AI, Holistic AI or IBM watsonx.governance.
• You need money when an AI error costs someone: an insurer such as Armilla or Munich Re aiSure, or AIUC-1 certification with AIUC.
• You need to control what an agent can reach: an identity product such as Microsoft Entra Agent ID, Auth0 for AI Agents or Vouched.
• Someone outside your company has to check what your agent did without trusting you: that is the gap APIR fills. Check an agent, free, or paper your first agent, free.

A team can trace with Langfuse, govern with Credo AI, insure with Armilla and still hand a buyer an APIR Evidence Pack. APIR takes events from an agent on any stack through one API call.

What tools keep an audit trail for AI agents?

Four kinds, for different readers. Observability tools such as LangSmith, Langfuse, Arize and AgentOps keep traces for the team running the agent. Governance platforms such as Credo AI, Holistic AI and IBM watsonx.governance keep governance records and audit trails for compliance teams. Identity products such as Microsoft Entra Agent ID and Auth0 log authentication and access. Open protocols, libraries and standards drafts give an agent a signed or hash-chained work history in different shapes (see who gives AI agents a tamper-evident work history at apir.ai). APIR keeps a signed, hash-chained log book that someone outside the company can verify without trusting it. Read from each company's own pages on 27 October 2026.

What is the difference between agent observability and an evidence record?

Observability is for the team that runs the agent: traces, evaluations and debugging, kept in that team's tool. An evidence record is for a reader outside the team, such as a buyer, an auditor or an insurer: signed, insert-only, hash-chained and timestamped by an outside authority, so it can be checked without access to the team's tools.

Is APIR a compliance platform?

No. APIR does not run a governance programme, write policies or audit anyone. Governance platforms such as Credo AI, Holistic AI and IBM watsonx.governance do that. Compliance teams can use APIR's record as evidence about an agent.

Does APIR insure AI agents?

No. APIR is not an insurer or a broker and has no underwriting partner. Armilla offers AI liability insurance, Munich Re offers aiSure, and AIUC certifies and insures AI agents. APIR keeps the record of what an agent did, which anyone, an underwriter included, can check.

Which AI agent audit tool is best?

It depends on who needs the answer. To debug your own agent, use an observability tool. To run an AI governance programme, use a governance platform. To transfer the financial risk, use an insurer. To control access, use an identity product. When someone outside your company must check what your agent did without trusting you, use an evidence record such as APIR.

Can an outside party verify LangSmith or Langfuse traces on their own?

The LangSmith and Langfuse pages read on 27 October 2026 describe traces kept for the team that runs the agent, with retention limits and self-hosting options. They did not describe signing the traces or letting an outside party verify them without access to the tool. Check their documentation for your case.