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Crunch Lab Builds out AI Intelligence Layer With Fresh $5M Capital

Crunch Lab, the core contributor to the decentralized artificial intelligence (AI) collective CrunchDAO, has raised $5 million in a strategic funding round, the company shared with Bitcoin.com News. The investment brings its total funding to over $10 million.

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Crunch Lab Builds out AI Intelligence Layer With Fresh $5M Capital

Crunch Lab Hits $10M Total Funding for Production-Ready AI Models

The round was co-led by Galaxy Ventures and Road Capital, with participation from Vaneck and Multicoin. In a release shared with Bitcoin.com News, the team said the new capital will accelerate platform development and expand the network’s reach into new industries.

Crunch Lab operates a decentralized network of more than 10,000 machine learning engineers and 1,200 PhDs who compete in structured modeling challenges, known as “Crunches”, to solve enterprise forecasting problems.

The platform has already delivered measurable results for major institutions. The Abu Dhabi Investment Authority (ADIA) Research Lab saw a 17% improvement in cross-sectional asset pricing predictions using the network. Separately, the Broad Institute of MIT and Harvard achieved breakthrough results in cancer gene research using Crunch’s computer vision models.

“AI today is constrained by hiring bottlenecks, siloed teams and an inability to scale effectively,” said Jean Herelle, CEO of Crunch Lab and CrunchDAO. “We’ve flipped that model. Instead of competing for scarce talent, we give enterprises secure access to all of it through a decentralized network.”

Investors back the project as a foundational layer for decentralized intelligence. “Crunch Lab is building an intelligence layer for global enterprises,” said Will Nuelle, General Partner at Galaxy Ventures. Thomas Bailey of Road Capital added that the protocol is positioned to capture value in the trillion-dollar AI market.

Earlier this year, CrunchDAO was selected for the Solana Incubator’s second cohort, further validating its technical approach. The network enables secure, crowdsourced model development that consistently outperforms traditional in-house teams.

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