While Silicon Valley chases the next AI infrastructure unicorn, January Ventures is making a different bet - backing underrepresented founders who understand legacy industries that AI could transform. The pre-seed fund writes checks for entrepreneurs applying artificial intelligence to healthcare, manufacturing, and supply chain operations, sectors where deep domain expertise matters more than pure tech credentials.
The venture capital world has AI fever, but January Ventures thinks everyone's looking in the wrong places. While most funds chase the latest large language model or GPU optimization play in San Francisco, this pre-seed fund is writing checks for founders who actually understand the industries AI could revolutionize.
"The most defensible AI companies are being built by founders with deep expertise in legacy industries," Jennifer Neundorfer, Co-Founder and General Partner at January Ventures, explained during a live TechCrunch Equity podcast recording at Disrupt 2025. The catch? "They're not getting funded."
It's a thesis that runs counter to the current investment frenzy around AI infrastructure. While venture dollars flood into foundation model companies and chip startups, Neundorfer argues the real opportunity lies with entrepreneurs who spent decades in healthcare, manufacturing, or supply chain before discovering how AI could solve their industry's thorniest problems.
The fund specifically targets underrepresented founders - a deliberate strategy in an industry where funding patterns often favor the usual suspects. According to All Raise data, only 2.3% of venture capital went to female founders in 2023, while diverse founding teams received even less. January Ventures sees this as both a market inefficiency and massive opportunity.
"Building different networks matters," Neundorfer told host Dominic-Madori Davis. Traditional VC networks tend to circulate around the same Stanford computer science graduates and former Google engineers. But the founders solving real problems in legacy industries often come from completely different backgrounds - former nurses building healthcare AI, manufacturing engineers developing predictive maintenance systems, or supply chain veterans creating inventory optimization tools.
This approach reflects a broader shift in early-stage investing. As AI capabilities become democratized through better APIs and open-source models, the competitive advantage increasingly lies in application and domain knowledge rather than pure technical prowess. A founder who understands hospital workflows intimately might build a more valuable AI healthcare company than someone who just knows how to fine-tune transformers.
