Zac Choi spent two decades building data and AI systems before spotting a problem few others saw coming: as businesses rushed to adopt artificial intelligence, their underlying data infrastructure wasn’t ready to support it. That foresight had already paid off once, after Choi built and sold his first startup, String AI, to a telecom partner. He has since founded Big Context & Company, a venture aimed at making enterprise data usable for AI agents rather than just human employees.
From Messy Systems to AI-Ready Data
Choi describes most business data as scattered across disconnected sources — point-of-sale systems, e-commerce platforms, retailer feeds — each organized differently and rarely built with AI in mind. Because large language models operate probabilistically while data management requires deterministic accuracy, he argues the two are structurally mismatched unless companies first clean and standardize their information. Without that groundwork, AI tools end up guessing at meaning rather than retrieving reliable answers, a mismatch Choi says explains why many AI implementations underdeliver.
A Career Built for the Moment
Choi’s path included stints at General Mills, Clorox, fintech company Green Dot, and McKinsey, where he led data transformation work for mid-market technology firms before several went on to become unicorns. That experience, paired with a Wharton data science background, convinced him to launch his own ventures. He also invests actively, having partnered with Alex and Leila Hormozi’s acquisition.com to make more than 30 startup investments over two years.
Choi credits much of his approach to a personal problem-solving method he calls the “Zero-One-Two-Three framework,” which pushes founders to question assumptions, return to first principles, seek outside opinions, and ultimately trust their own judgment to move quickly.