Angela Gao Co-Founds Fearn, an AI-Native Patent Prosecution Firm, Raises $5.5 Seed Funding
Fearn, a patent generation platform relying on artificial intelligence, announced on Wednesday the raising of $5.5 million in a seed funding round from Kindred, a16z Speedrun, and other investors to expand Fearn's platform and pivot into an AI-native patent prosecution firm. It's "not a software tool sold to lawyers, but a firm that employs its own former Big Law patent experts and runs its drafting through a system called FearnOS," as reported in Tech Funding News on September 23, 2026.
"A conventional patent application eats 30 to 40 hours of a lawyer’s time and costs somewhere between $18,000 and $40,000. Fearn thinks that math is broken, and it’s built an entire law firm to prove it," TFN noted, continuing that Fearn "charges flat fees, such as 2,500 for a provisional filing, $9,000 for a non-provisional, with a refund if no claims are allowed."
Founded by former lawyer Han Kim and AI specialist Angela Gao, Fearn pivoted from selling software to law firms to directly serving startups. Fearn is a modern high-touch patent prosecution firm that is "killing the billable hour." As stated on Fearn's website, "Fearn’s team is former Big Law—from the people who did the work, not the partners who signed off on it."
The San Francisco startup's raise is from Kindred Ventures, a16z Speedrun, Designer Fund and Essence VC, not to sell software but to launch a firm that employs its own former Big Law patent experts and runs its drafting through its own system, called FearnOS.
"At Fearn, we marry the latest advances in computer science with the legal expertise of our former Big Law patent prosecutors. Our approach results in top-tier patents, turned around in days. Our work is always reviewed by a former Big Law patent prosecutor. In addition, we charge only fixed fees, so you'll never be surprised by your legal bill."
Angela Gao is the CTO and cofounder of Fearn. Previously, Angela conducted machine learning research at Google. Angela received her B.S.E. in electrical engineering and computer engineering from Carnegie Mellon University. Angela has published in the top computer science conferences and journals, including NeurIPS, CVPR, and TMLR.
Angela received her PhD from Caltech in computational and mathematical sciences. Her PhD thesis focused on physics-based AI and inverse problems, under the supervision of Dr. Katie Bouman.
This reporting is drawn from various articles and websites, including Fearn, Forbes, Tech Funding News, Andreessen Horowitz (a16z), and Law360.
