The Founding Insight
Watt was founded by the engineers behind petabyte-scale reasoning systems at some of the world's most demanding institutions. Our CTO spent 15 years building data infrastructure for systematic trading — designing the same kind of non-deterministic reasoning systems that make LLMs so powerful, and so hard to build on top of.
The founding insight was simple: AI agents don't work like humans. They don't read a contact record and make a judgment call. They traverse graphs of interconnected signals. Legacy data tools were never built for that. We built something that was.
We unified 25,000+ upstream data sources across our broker network into a single traversable data model. Not aggregated fields — raw signals. The result is a data layer that AI agents can actually reason on, in milliseconds, at any scale.
Watt doesn't have data others don't have. What's different is how it's represented. Legacy tools compressed raw signals into ~300 pre-aggregated fields, filtered before you ever see them, designed for human analysts. Watt took the same underlying data and made it traversable by an AI agent — exposing 81,000+ signals per person instead of 300. One competitor spent $500K and six months trying to replicate the joining layer. They became a Watt customer instead.
250M+
Verified people
60M+
Businesses covered
81,000+
Total signals in graph
65B
Graph nodes
16T
Pre-computed relationships
The Team
Backed By
We're a small team building something that's never been built before. If that sounds interesting, we'd love to talk.