Hebbia

Finance professionals spend hours reading hundreds of pages of filings, contracts, and reports to pull data points and write analyses, with critical details buried across sprawling document sets.

AI agents that ingest thousands of documents, complete entire research and analysis workflows in minutes with full citations, and output structured answers a human analyst would trust.

AI models can finally reason across 100,000+ page document sets with accuracy high enough for regulated industries — shifting from assisting knowledge workers to actually doing the work end-to-end.

$13M in profitable revenue at Series B, blue-chip asset managers say removing Hebbia would cause employees to quit, and the platform is embedded in daily workflows across finance and law.

George Sivulka (CEO, Stanford PhD dropout in AI and physics) built Hebbia from a dorm room, combining frontier AI research with deep understanding of how knowledge workers actually think and reason.