Hebbia, an AI startup that uses generative AI to search large documents and return answers, has secured nearly $100 million in a Series B funding round led by Andreessen Horowitz. The company, founded in 2020 by George Sivulka during his PhD studies in electrical engineering at Stanford, aims to revolutionize information retrieval for professionals across various domains.

The Problem Hebbia Solves

Hebbia’s inception was inspired by Sivulka’s friends working in the financial industry. They spent long hours sifting through dense documents like SEC filings, seeking critical information. Recognizing the potential for AI to streamline this process, Sivulka set out to create a solution that could save professionals valuable time and enhance productivity.

How Hebbia Works

Hebbia’s AI engine can analyze billions of documents simultaneously, including PDFs, PowerPoints, spreadsheets, and transcripts. It then provides specific answers, eliminating the need for manual searches. While the startup primarily caters to financial service firms, including hedge funds and investment banks, its product could also benefit law firms and other professional sectors.

Series B Funding and Valuation

The recent Series B funding round, led by Andreessen Horowitz, valued Hebbia between $700 million and $800 million. Although the exact valuation remains unconfirmed, the company’s growth trajectory is evident. Hebbia had previously raised $93 million out of a hoped-for $100 million, and this round brought it close to the $100 million mark.

Industry Landscape and Competition

Hebbia’s product shares similarities with Glean, another software solution that fetches information in plain English from various business applications. In February, Glean raised a staggering $200 million in a Series D round, achieving a valuation of $2.2 billion.

Future Prospects

With this substantial funding, Hebbia is poised to expand its reach and further enhance its AI capabilities. As professionals increasingly rely on data-driven insights, Hebbia’s innovative approach to document search positions it well for continued success.