San Francisco-based Athena has secured $2.5 million in a pre-seed funding round led by a16z Speedrun, the 12-week accelerator programme run by Andreessen Horowitz, as the start-up looks to reshape transactional legal services through an AI-native operating model.
The funding round, announced on 3 November 2026, will support Athena’s expansion in commercial real estate transactions and its growth into additional property types, geographies, and other areas of transactional law, including M&A and venture capital financings. The company was co-founded in August by former Legora employees Cem Ucan and Kieran John Keenan, alongside lawyer co-founders Karen Abesamis and Juan Soto. Ucan serves as CEO, while Keenan is chief technology officer.
At the heart of Athena’s model is a deliberate departure from how most legal AI companies have approached the market. Rather than selling software licences to incumbent law firms, Athena operates as an affiliated law firm supported by its own proprietary technology company. Its AI agents draft and prepare complex transaction documents, while experienced attorneys at the affiliated firm—Athena Circle—review, negotiate, and take responsibility for the final work product. The affiliated law firm charges a fixed fee per transaction, typically 30% to 50% below what clients have paid on recent deals, according to the company.
Ucan said the approach was born from a recognition that legal AI tools had become significantly more capable without changing the underlying economics of legal practice. “Most legal AI companies sell tools to traditional law firms. We took a different approach. Our AI works hand-in-hand with a law firm designed around it from day one, with experienced attorneys focused on the judgment and negotiation that actually move deals forward,” he said. Keenan added that the measure of the platform’s success is how quickly an attorney can review an AI agent’s work and confidently stand behind it. “A draft produced in minutes can still leave a lawyer with hours of work. Making that review more efficient is how our platform helps us deliver faster legal services with the quality clients expect from Big Law,” he said.
Early traction appears to have been swift. In its first five weeks, Athena secured 16 account relationships across signed engagements and design partnerships, representing approximately $700,000 in committed legal fees. The company has since reported signing 22 clients in the two months following launch and says its platform has cut attorney review time by more than 70%, turning around one purchase agreement in under 48 hours. Keenan stated on LinkedIn that the firm went “from zero to seven figures in revenue” within two months.
Troy Kirwin, partner at a16z Speedrun, said clients will continue to demand experienced professionals take responsibility for legal tasks even as AI becomes more capable. “Athena is building around that need, with a system that can improve through real legal work and a team obsessed with scaling fast,” he said. The founding team’s pedigree lends credibility to that ambition. Ucan spent years in Big Law before moving into legal innovation at Baker McKenzie and later Legora, while Keenan built Legora’s evaluation infrastructure and worked on LLM quality. Founding engineer José Braz also came from Legora, where he built the company’s legal research agent.
Athena enters a competitive field that includes well-funded legal AI software providers such as Harvey and Legora. Its fixed-fee model incentivises speed, but sustaining that pricing through complex, prolonged negotiations—and retaining clients against rivals making similar promises—remain open questions. The company’s near-term growth is also tied to commercial real estate refinancing cycles, with roughly $2.5 trillion of US commercial mortgages falling due between 2025 and 2027, a wave the founders expect to drive deal activity. For now, Athena’s bet is clear: that the next generation of legal services will be won not by those who sell AI to lawyers, but by those who build the law firm around the AI.
