The Good Tech Companies - Why Crunch Lab's $5M Raise Could Transform How Enterprises Build AI Models

Starting point is 00:00:00 This audio is presented by Hacker Noon, where anyone can learn anything about any technology. Why Crunch Labs' $5 million raise could transform how enterprises build AI models. By a Sean Pondy, how Crunch Lab plans to replace $100 million hiring budgets with 10,000 crowdsourced engineers. Greater than can a network of anonymous contributors outperform elite in-house teams at a greater than fraction of the cost? Crunch Lab is betting $5 million that the answer is yes. On October 7th, 2025, Crunch Lab announced it secured $5 million in funding Co-ledby Galaxy

Starting point is 00:00:36 Ventures and Road Capital, with participation from Vanek and Multicoin. The round, which closed in June, brings the company's total funding to $10 million after a $3. 5 million seed round in 2024. The company builds what it calls an intelligence layer for decentralized AI, connecting enterprises with a network of more than 10,000 machine learning engineers and 1,000. 200 pH disthrough its platform, Crunch Dow. The concept challenges how organizations approach AI development. Instead of spending years recruiting specialists or building internal teams, enterprises submit problems as encrypted modeling challenges. Contributors compete to build solutions,

Starting point is 00:01:16 and rewards flow to whoever delivers the best results. The Abu Dhabi Investment Authority, Adia Research Lab reported a 17% improvement in cross-sectional asset pricing predictions using this method. The Broad Institute of MIT and Harvard used the network for cancer gene research with computer vision. A global investment bank now runs mid-plus-1, a crowdsourced pricing engine for FXOTC markets, in production. The funding reflects growing interest in decentralized approaches to eye infrastructure. Galaxy Ventures, Road Capital, Vanek, and Multicoin have all made bets that collective intelligence models can compete with centralized alternatives. The company was also selected for the Solana Incubator's second cohort earlier in 2025, and the platform operates on Solana's

Starting point is 00:02:03 blockchain. The economics of talent scarcity. Hiring specialists in machine learning costs money. A senior ML engineer in the United States commands an average salary between $150,000 and $250,000 per year, according to industry data. Building a team of 10 to 20 engineers to tackle predictive modeling can easily exceed $2 million annually before factoring in infrastructure, benefits, or retention costs. Enterprises in finance, health care, and technology compete for the same limited pool of candidates. Crunch Labs model offers a different path. Instead of hiring full-time staff, companies post-modeling challenges. Thousands of engineers participate, and organizations pay only for results. Gene Hirel, CEO of Crunch Lab and Crunch Dow, said, AI today is constrained.

Starting point is 00:02:52 by hiring bottlenecks, siloed teams and an inability to scale effectively. We've flipped that model. Instead of competing for scarce talent, we give enterprises secure access to all of it through a decentralized network. The approach mirrors crowdsourcing platforms like Kaggle, but with a focus on production deployment rather than competition alone. Companies submit real problems, not academic exercises. Contributors work with encrypted data, so proprietary information stays protected.

Starting point is 00:03:20 The network then aggregates predictions from multiple models to generate final outputs. Horel added, this isn't theoretical hype, it's proven. When thousands of practitioners compete, you uncover solutions even the best internal teams miss. Proven performance in high-stakes environments. Results matter more than promises in AI. Crunch Lab points to three deployments as evidence its method works. The first involves Adia Lab, the research division of the Abu Dhabi Investment Authority. Adia manages more than $900 billion in assets, making it one of the largest sovereign wealth

Starting point is 00:03:54 funds in the world. The lab used Crunchdeo's network to improve predictions for asset pricing across different securities. The 17% accuracy gain translates to better portfolio decisions and risk management at scale. The second case involves the Broad Institute of MIT in Harvard, a research organization focused on genomics and biomedical science. The Institute used the network for cancer gene research, applying computer vision techniques to analyze data. The press release describes the results as a breakthrough, though no specific metrics were disclosed. Cancer research involves identifying patterns in vast datasets and machine learning models help researchers detect relationships that might otherwise go unnoticed. The third deployment is mid-plus-1,

Starting point is 00:04:39 a pricing engine for foreign exchange over-the-counter, OTC markets. OTC trades happen directly between parties, without exchanges, and pricing depends on real-time supply and demand. A global investment bank, which Crunch Lab did not name, now uses mid-plus-1 in live trading. The engine relies on crowdsourced models to calculate mid-market prices, the midpoint between buy and sell quotes. Accurate pricing reduces transaction costs and improves execution for large trades. Why investors see an infrastructure play. Venture capital in AI has tilted toward infrastructure in recent years. Investors pour money into platforms that enable other companies to build applications, rather than applications themselves. Crunch Lab fits this category. Will Newell, General Partner at Galaxy Ventures, said, CrunchLab is building an intelligence layer for global enterprises.

Starting point is 00:05:32 Whether predicting asset prices, optimizing energy demand, or advancing healthcare diagnostics, CrunchDAO's crowdsourced models unlock smarter, faster decision-making. Thomas Bailey of Road Capital echoed the sentiment. Greater than we believe Crunch Lab represents one of the most compelling attempts to greater than connect global quants with enterprises at scale. AI is a trillion dollar greater than market, and open protocols like Crunch are positioned to capture it. The framing positions Crunch Dow is infrastructure, not a vertical solution. The platform could serve finance, health care, logistics, energy, or any field where

Starting point is 00:06:08 predictive modeling drives value. The choice of investors also signal strategy. Galaxy Ventures operates as the venture arm of Galaxy Digital, a firm focused on digital assets and blockchain technology. Road Capital and Multi-Coin both invest in decentralized networks and crypto infrastructure. Vanek, known for exchange traded funds, has expanded into digital assets. The investor group suggests Crunch Lab sees itself as part of the decentralized web, not traditional software as a service. Risks and questions about decentralized AI. The concept raises questions. First, how does the platform ensure quality control when thousands of anonymous contributors

Starting point is 00:06:49 submit models? Crunch Dow uses a performance-based reward system, so contributors earn tokens based on accuracy. But one bad model in a production environment can cause damage. Enterprises need guarantees, not probabilities. Second, data security remains a concern. Crunch Lab encrypts data before sharing it with contributors, but encryption methods vary in strength. Homomorphic encryption, which allows computation on encrypted data, is still developing and can be slow. Zero knowledge proofs offer another path, but they add complexity. The company has not disclosed which methods it uses or how it audits security. Third, the platform depends on network effects. With 10,000 contributors, Crunch Dow has enough participants to generate useful results. But maintaining

Starting point is 00:07:36 Engagement over time is difficult. Contributors need incentives to keep participating, and rewards must feel worthwhile. If the network shrinks, the quality of predictions could decline. Fourth, regulatory uncertainty looms over decentralized platforms. Enterprises and finance and healthcare operate under strict compliance rules. Using aid centralized network with anonymous contributors might conflict with Know Your Customer, K-YC, or anti-money laundering, AML requirements. will need to navigate these rules as it scales the path forward for collective intelligence crunch lab plans to expand beyond finance and biomedical research the company did not specify which industries it will target next but predictive modeling applies broadly energy companies forecast

Starting point is 00:08:23 demand logistics firms optimize routes retailers predict inventory needs any organization that relies on forecasting could benefit from better models the solana incubator selection adds credibility. Solana is one of the faster blockchains, processing thousands of transactions per second with low fees. Building on Solana allows Crunch Dow to handle high transaction volumes without cost prohibitions. The incubator provides technical support and connections to the Solana ecosystem, which could help with partnerships and integrations. The $5 million round will fund platform development and team expansion. Crunch Lab did not disclose current headcount or hiring plans, but scaling aid centralized network requires engineering resources.

Starting point is 00:09:07 The company must build tools for enterprises to submit challenges, manage data encryption, coordinate contributors, aggregate predictions, and monitor performance. Each step involves technical complexity. Competitors exist in this space. Numeri, founded in 2015, operates a similar model for hedge fund predictions. Ocean Protocol builds data marketplaces with blockchain infrastructure. Fetch. I focuses on autonomous agents for decentralized systems. Crunch Lab differentiates by emphasizing production deployments and measurable results, not just research or speculation.

Starting point is 00:09:43 Final thoughts. Crunch Labs model offers a practical test of whether decentralized networks can deliver results that matter. The 17% accuracy improvement for Adia Lab is measurable. The deployment of mid-plus-1 in live trading is real. The Broad Institute breakthrough, while less quantified, comes from a respected research organization. These are not thought experiments or white papers. They are production systems handling consequential problems. The question is whether this approach scales across industries and use cases. Financial modeling and biomedical research are natural fits for crowdsourced AI. Both fields have large datasets, clear performance metrics, and tolerance for experimentation. But will the model work in manufacturing, where failures cause

Starting point is 00:10:27 downtime, or in autonomous vehicles where mistakes endanger lives, or in legal analysis, where accountability matters, the $10 million in funding gives Crunch Lab time to find answers. The investor group brings credibility and connections in decentralized infrastructure. The network of 10,000 contributors provides a foundation to build on, but the company must prove it can maintain quality, protect data, navigate regulations, and keep contributors engaged over time. If Crunch Lab succeeds, it could change how enterprises think about AI development. Instead of hoarding talent, organizations could tap into global networks. Instead of building models from scratch, they could access collective intelligence. The shift would redistribute

Starting point is 00:11:11 value from centralized teams to decentralized contributors and from proprietary systems to open protocols. That outcome depends on execution. Crunch Lab has results to point to, funding to deploy, and a network to leverage. Now it must scale without breaking what works. Don't forget to like and share the story. This author is an independent contributor publishing via our business blogging program. Hacker Noon has reviewed the report for quality, but the claims here and belong to the author. Hashtag D.Y.O. Thank you for listening to this Hackernoon story, read by artificial intelligence. Visit hackernoon.com to read, write, learn and publish.

The Good Tech Companies - Why Crunch Lab's $5M Raise Could Transform How Enterprises Build AI Models

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