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TAB is an independent platform for testing, verifying, and benchmarking AI agents and models. It runs the same battery of behavioral benchmarks against everything it evaluates and reports what actually happened, across safety, security, sycophancy, error recovery, agentic commerce, and governance, spanning 340+ benchmarks. TAB does not work for the labs it tests: scoring uses an independent judge, the methodology is published, and the calibration data is public, so teams can verify how an agent behaves before it reaches production, customers, or money, instead of trusting a vendor's own claims.

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