Most AI legal tools fit smoothly into standard document workflows, but patent work is different. A single mistake in a claim chart can cost a client the chance to bring a product to market. Owning a particular patent can determine whether a company can enter or exit a market. Because of these high stakes, many AI vendors have stayed away from this area.
Patlytics was created to tackle this problem. Co-founders Paul Lee and Arthur Jen built the platform to help with the complex, judgment-heavy work patent attorneys do, such as prosecution, litigation, and licensing negotiations.
Patlytics has raised $40 million in a Series B round led by SignalFire, with support from N47, Myriad Venture Partners, Relativity, Alumni Ventures, Antiportfolio Ventures, and BAM Corner Point. In less than three years since its founding, the company has raised about $65 million in total.
Based in New York, the company builds AI software that covers the whole patent process. This includes drafting applications, checking for infringement, doing invalidity research, and managing portfolios. More than 40% of Am Law 100 firms use Patlytics, as do corporate IP teams at companies like Rivian, Xerox, and Canon.
Customers say they have cut project time by up to 80%, saved more than $30,000 per claim chart, and gained back about 15 hours per patent application. Patlytics attributes these results to its complete workflow system, not just swapping out single tools. For example, Rivian’s IP team uses the platform to turn raw information into draft sections that attorneys can edit right away.
Patlytics competes with companies like Solve Intelligence, Patentext, and DeepIP. Unlike its competitors, Patlytics offers a wider platform that covers everything from invention disclosure to litigation and portfolio management, all in one place. Its guided workflow helps firms get results faster, even if they do not have their own AI experts.
The new funding will go toward three main goals: creating a shared workspace where law firm and corporate IP teams can work together on patent projects; developing AI agents that can handle drafting, research, and portfolio triage on their own; and improving tools for chemistry and biology, so the platform can better handle sequence and chemical structure tasks in prosecution, search, and analysis.
