ProofOS runs AI agents on real production websites — not sanitized sandboxes. We measure what actually happens when an agent hits a live login form, a dynamic checkout flow, or an authentication gate. The numbers are honest. The scores are final.
We run agents on actual production websites — not static HTML or sandboxed replicas. Real logins, real forms, real consequences. Every task runs against the live internet.
We intercept only the final submission request. Agents interact with live sites freely until that last click — then we verify what would have been sent without ever letting it through. No side effects. No data written. Just honest measurement.
Every task gets verified by DOM matching, LLM judge, and automated grading. We don't just check if the agent got to the right page — we check if it completed the full workflow correctly.
The best frontier models hit 65%+ on traditional benchmarks. On ClawBench V2 — 144 live websites, 130 real tasks — the best agent scores 44.6%. Most don't break 33%. That 20-point drop is why you can't trust benchmark scores without knowing how they were measured.
We built ProofOS because the benchmark numbers you're making decisions from are lying to you. Not intentionally — but the methodology is broken. Testing an AI agent on a static sandbox tells you nothing about how it will perform on a live website with real authentication, dynamic content, and rate limits.
ProofOS exists to give developers, labs, and enterprises the honest data they need. Not a number. Not a demo. The real score.
ProofOS is the operating layer for AI agent evaluation — infrastructure that runs the benchmarks, scores the results, and makes the data actionable for developers and enterprises who need to know what their agents can actually do.