Fearn Raises $5.5 Million to Build an AI-Based Patent Firm for Startups
Fearn Raises $5.5 Million to Build an AI-Based Patent Firm for Startups
  • Dan Yoo
  • Published 2026.09.24 14:16
  • Comments 0
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Fearn co-founders Angela Gao (left) and Han Kim. The company has launched an AI-based patent firm for startups after raising $5.5 million. / Courtesy of Fearn

San Francisco-based patent firm Fearn launched on September 23 with $5.5 million in funding to offer startups fixed-fee patent drafting and prosecution services. The company combines patent professionals with its own AI drafting system and says it can typically file provisional applications within three business days. Kindred Ventures, a16z Speedrun, Designer Fund and Essence VC backed the funding round.

Co-founders Han Kim, a former patent practitioner at Morrison & Foerster, and Angela Gao, who holds a doctorate in computer science and AI, initially developed software for law firms. They subsequently built Fearn as a firm using that technology in its own legal work. Its system, FearnOS, connects patent claims with supporting text, figures and technical material while recording attorney edits and document versions. Fearn says a patent professional reviews every application.

The firm lists a $2,500 fee for a provisional application and $9,000 for a non-provisional application, including U.S. Patent and Trademark Office fees. It says its guarantee refunds the non-provisional drafting fee if an application it carries through examination receives no allowed claims. The precise conditions of that guarantee would matter to clients assessing the offer, particularly because patent examination can involve revisions over an extended period.

Fearn says clients in software, hardware, robotics and biotechnology are already using its services. It cited game studio Iconic, defense technology company Photon Spear and cancer-vaccine developer Serova Bio as examples. These accounts illustrate the company’s intended market, though the announcement does not provide independently measured comparisons of filing quality, total legal cost or eventual patent outcomes.

“If AI makes the work faster, the client should feel that in the turnaround time and the bill,” Kim said. Fearn’s model tests whether gains from AI-assisted drafting can be reflected in predictable fees while maintaining the legal review and technical detail that patent applications require. Its longer-term plans include tools for international filings, responses to patent-office objections and portfolio management.


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