Vals AI
Independent, real-world task benchmarks that catch what public leaderboards miss.
About
Vals AI is an independent AI benchmarking startup founded in 2024 by Rayan Krishnan and Langston Nashold. It builds private, real-world task benchmarks for law, finance, and coding rather than public static test sets, with human evaluation over the model outputs. In August 2026 it announced a $40M Series A led by a16z at a $400M valuation, reflecting demand for trustworthy model evaluation as labs ship ever-faster model updates.
The honest caveats: private benchmarks are hard for outsiders to audit — you trust their test sets and graders without the reproducibility of open benchmarks. The company is young, so its benchmark suite is narrower than community standards like LMArena. Their Vals Smith coding benchmark tool targets this gap. Still, for teams deciding which model to put in production, independent real-world task testing beats stale public leaderboards.
What it can do
- Private real-world task benchmarks
- Human-in-the-loop evaluation
- Coding benchmarks via Vals Smith
- Law and finance domain task tests
- Independent model comparison reports
Setup
Sign up on the Vals AI platform to request evaluations or benchmark access.
Prerequisites
Models or evaluation use cases to test; some benchmarks are paid.
Use cases
Works with
Trust score — 9/10
Scored 9/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 85; Trending score 86/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.