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# Vals, backed by Andreessen Horowitz, is looking to become the gold standard for AI benchmarking

**[TechCrunch](https://daily.dev/sources/tc)** · 5 min read · 0 upvotes · 0 comments

## Summary

Vals AI, a startup founded in 2024, is building independent benchmarking for AI models by testing them on real-world industry tasks in law, finance, coding, cybersecurity, biosecurity, and mental health rather than relying on publicly available academic tests that can be gamed. The company recently raised $40 million in a Series A led by Andreessen Horowitz, following an earlier seed round from 8VC and Bloomberg Beta. Revenue has grown eightfold year over year, and staff has tripled from eight to 25 people, with plans to add more and relocate to a larger office. Vals also launched a program offering model evaluations to federal agencies, and co-founder Rayan Krishnan argues that as AI companies go public, rigorous third-party benchmarking will become central to investment decisions and public filings.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://techcrunch.com/2026/09/19/vals-backed-by-andreessen-horowitz-is-looking-to-become-the-gold-standard-for-ai-benchmarking>

## Questions this post answers

### How much funding did Vals AI raise in its Series A round and who led it?

Vals AI raised $40 million in a Series A round led by Andreessen Horowitz. This followed an earlier seed round led by 8VC and Bloomberg Beta. The startup was founded in 2024 by Rayan Krishnan and has grown revenue eightfold year over year while tripling its staff from eight to 25 people.

_Developers picking AI models for production can track how benchmarking startups like this evolve on daily.dev._

### Why do some AI benchmarks fail to accurately measure modern AI model capabilities?

Many legacy benchmarks are outdated and rely on publicly available test materials, which allows companies to train their models directly against those tests, effectively cheating on the exam. Vals AI addresses this by keeping its test materials private and evaluating models on real-world task completion in domains like law, finance, and coding rather than abstract knowledge tests.

_Anyone comparing AI models by their benchmark scores can follow benchmarking methodology debates on daily.dev._

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Tags: [#ai](https://daily.dev/tags/ai), [#startup](https://daily.dev/tags/startup), [#llm](https://daily.dev/tags/llm)

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