# Goodfire Raises $150M Series B for AI Interpretability

> Goodfire has raised a $150 million Series B at a $1.25 billion valuation, led by B Capital, to scale its work on AI interpretability, the effort to open the black box of neural networks and understand what is actually happening inside them. The round drew a long list of backers including DFJ Growth, Salesforce Ventures, Menlo, and Lightspeed. What makes Goodfire more than a research curiosity is that its methods are producing concrete results. The company says interpretability-informed training cut model hallucinations by 50 percent, and by reverse-engineering biological models it helped identify novel Alzheimer's biomarkers, the same reverse-engineering approach that also recovered chess concepts from AlphaZero. It has partnerships with the Arc Institute, Mayo Clinic, and Microsoft. Interpretability has often been treated as a purely academic pursuit, so a startup commercializing it at this valuation is a meaningful signal. The bet is that understanding and editing model internals will become standard practice, both for making systems safer and more controllable and for using them as instruments of scientific discovery, turning a safety-flavored research agenda into a business that enterprises actually pay for.

_Section: [AI Funding Tracker](https://www.wortins.com/funding) · Source: Goodfire AI · Published Friday, July 10, 2026_

## Wortins' read

Goodfire has raised a $150 million Series B at a $1.25 billion valuation, led by B Capital, to scale its work on AI interpretability, the effort to open the black box of neural networks and understand what is actually happening inside them. The round drew a long list of backers including DFJ Growth, Salesforce Ventures, Menlo, and Lightspeed. What makes Goodfire more than a research curiosity is that its methods are producing concrete results. The company says interpretability-informed training cut model hallucinations by 50 percent, and by reverse-engineering biological models it helped identify novel Alzheimer's biomarkers, the same reverse-engineering approach that also recovered chess concepts from AlphaZero. It has partnerships with the Arc Institute, Mayo Clinic, and Microsoft. Interpretability has often been treated as a purely academic pursuit, so a startup commercializing it at this valuation is a meaningful signal. The bet is that understanding and editing model internals will become standard practice, both for making systems safer and more controllable and for using them as instruments of scientific discovery, turning a safety-flavored research agenda into a business that enterprises actually pay for.

## Source

[Read the full story at Goodfire AI](https://www.goodfire.ai/blog/our-series-b)

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