Series A: Always a Higher Peak

Vals AI argues that AI development has advanced faster than independent evaluation methods, leaving existing benchmarks vulnerable to rapid saturation, training-data leakage, and conflicts of interest when model developers assess their own systems. The company aims to provide independent, reproducible benchmarks for professional tasks in fields such as law, finance, engineering, and medicine, using private test sets and partnerships with domain institutions to maintain measurement integrity. It says its evaluations have been cited by major AI labs, used by enterprises selecting models, and supported AI policy work in government, while reporting significant revenue, customer, and team growth. Vals announced a $40 million Series A funding round at a $400 million valuation led by Andreessen Horowitz, alongside the general availability of Vals Smith for creating coding benchmarks from GitHub repositories, new frontier-risk benchmarks including cyber and mental-health work, and a rebuilt Vals platform and expanded index.

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