BenchAudit: independent credibility scoring for agent benchmarks

Third-party audit of AI agent benchmark scores

Problem

Engineers at newer startups report that agent companies buy benchmarks to prove reliability to customers, which looks a lot like pre-2008 credit ratings where the rated party pays the rater. Buyers approving agent products can't tell whether scores are trustworthy or what would actually get a product over the line.

Solution

An independent benchmark audit and reproduction service: rerun public agent benchmarks as a third party, record reproducibility, evidence of test-set tuning, evaluation costs, and failure modes, and publish a credibility score with raw logs. Buyers can request audits of specific products, all results stay public, and the methodology is open source.

Users

Enterprise tech leads procuring or approving AI agents, security and compliance teams, and customers of agent startups

MVP

Independent reruns of 3-5 mainstream agent benchmarks; public logs and configs for every run; reproducibility and bias observations; one-page credibility report

Revenue

Report subscriptions; custom audits per product; open methodology as a trust signal

Why now

Agent procurement is booming while independent evaluation is scarce; the conflict-of-interest problem was just publicly raised, making the timing right