Vigil Labs AI Raises $5.7 Million To Build Bionic Traders

Vigil’s founder and CEO, Kole Lee, dropped out of Stanford to start what may become the world’s largest hedge fund, powered by real time data from proprietary sources, and a reasoning system specifically trained to advise and augment human traders. His first customer is himself. Lee is literally betting his fortune on his startup.

Lee is a former teenage magician who once performed for Silicon Valley luminaries, he traces his interest in computing back to his grandmother, one of UCLA’s first Fortran programmers. In high school, he started building his personal wealth by trading equities, but soon gravitated toward crypto. He interned at Pantera Capital, led Stanford’s Blockchain Club, and turned a small personal crypto stake into a fortune. “I’ve always believed that markets reward intelligence and adaptability,” he said. “AI is the purest way to scale those qualities.”

In 2024, Lee made headlines when he persuaded the student-run Blyth Fund to allocate seven percent of its portfolio to Bitcoin. At the time, Bitcoin was trading at roughly $42,000. The move drew national attention and over a million views across social platforms. “It was a lesson in conviction and timing,” Lee told me. “Markets are intelligence games. The edge comes from who can see the signals first and act with confidence.”

The key to the system is where Vigil gets its data. It supplements traditional sources that everyone uses with a proprietary combination of data gleaned from diverse sources, like social media, Reddit, and predictive markets, the sum of which, Lee admitted, is their own “black box.” Instead of training an LLM, the company is building infrastructure to harness existing AI advances but with a specialized reasoning system for trading. “The result” said Lee in an interview yesterday, “is continuous, superhuman coverage of global markets, surfacing opportunities no single analyst could monitor.”

Comparison with Wall Street’s famous “black box” systems is inevitable. Firms like Renaissance Technologies and Citadel have long cultivated reputations for secretive algorithmic models that churn through massive datasets to identify patterns and generate trades. Vigil sits in the same competitive frame, but its founder argues the approach is fundamentally different. Their reasoning system is built to focus and advise traders, making them “bionic,” able to spot, and measure opportunity and risk.

The company’s longer-term vision is to build a “prediction engine” that learns directly from financial markets, which serves as the reward system. Every tick of data is a feedback loop, teaching the AI how to adapt and improve. If successful, Vigil would blur the line between algorithmic trading and applied machine reasoning.

“Applying AI to solve the markets is among the largest opportunities in the intelligence era,” said Koko Xs, Cofounder at Nova. “Every generational technology company has a core cash engine that fuels compounding innovations, and a new generation of missionary hedge funds like DeepSeek are emerging as the dominant tech players. We hold deep conviction in Kole’s magical ability to shape markets and the future.”

The small founding team of four blends computer science and trading backgrounds. Chief Product Officer Daniel Nunes worked at the intersection of crypto and analytics. Newly appointed Chief Technology Officer Calder White has a diverse background in programming, system-level engineering, and real-world trading. By 20, he had helped scale Tensor, the leading NFT exchange on Solana, to process over $3B in annual volume.

Lee is hoping the system will work so well that he won’t have to take another dime from investors, and instead will self-fund. “It comes down to who adapts fastest,” Lee said. “by changing the timing and quality of information traders get, AI will turn the smartest human traders into super traders ”

Nova led the seed round, with participation from Lux Capital, Pantera Capital, SV Angel, Soma Capital, Valor Equity Partners, Jack Altman, Kevin Hartz, Cyan Banister, Micky Malka, and several prominent AI researchers.