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The AI industry has a talent problem. Building world-class predictive models traditionally requires assembling elite teams, a process that costs upwards of $100 million and takes years. But what if you could tap into the collective intelligence of 10,000+ machine learning engineers instead?
Today, we're announcing that Crunch Lab has raised $5 million in a strategic funding round co-led by Galaxy Ventures and Road Capital, with participation from VanEck and Multicoin Capital. This brings our total funding to $10 million and validates a fundamentally different approach to AI: one that's decentralized, meritocratic, and already delivering measurable results in production.
The demand for high-quality predictions spans from finance to healthcare to energy. Yet the traditional model of building in-house AI teams faces critical bottlenecks:
To tackle these, we've built a decentralized network that gives enterprises secure access to all of it through structured modeling challenges called Crunches.
Our crowdsourced approach is driving real breakthroughs for world-class institutions:
When you transform enterprise problems into encrypted modeling challenges and let thousands of practitioners compete, you uncover solutions even the best internal teams miss.
The power of CrunchDAO lies in three core principles:
Our investors understand that Crunch is the infrastructure for a new paradigm:


This funding accelerates our mission on multiple fronts:
At the heart of Crunch Lab is CrunchDAO, our decentralized protocol. It connects over 10,000 data scientists and AI engineers worldwide, including 1,200+ PhDs, through structured challenges that consistently outperform traditional in-house approaches.
The protocol handles everything from secure model submission to privacy-preserving data transformation to automated reward distribution while protecting both contributor IP and enterprise data. It's infrastructure designed for collective intelligence at scale.
The era of hiring bottlenecks and siloed AI teams is ending. The future belongs to collective networks that can harness global talent, adapt continuously, and deliver results that single teams simply cannot match.
As our CEO Jean Herelle puts it: "When thousands of practitioners compete, you uncover solutions even the best internal teams miss."
We're building the intelligence layer for the next generation of enterprise AI. And we're just getting started.