IPRally, a startup based outside Finland, has raised € 2 million in seed funding, aimed at solving the patent discovery problem.
Leading the round is the involvement of existing pre-seeded backer Icebreaker VC by Joine Capital and Spintop Ventures. This is brought to a total of € 2.35 million by the company established by 2018.
Founded by co-CEO Sakari Arvella, who has 15 years of experience as a patent lawyer, IPRally Created a knowledge graph to better understand the patent’s technical details and help humans train more efficiently through existing patients. The premise is that a graph-based approach is more suited to patent search than simple keyword or freeform text search.
This is because, Arvela argues, every patent publication can be distilled to a simple knowledge graph that “resonates” with IP professionals’ way of thinking and is infinitely more machine readable.
“I founded IPReally in April 2018 after a year of bootstrapping and proof-of-concept with my co-founder and CTO Juho Kallio,” he tells me. “Prior to this, I had digested the graph’s approach myself for almost two years and had the courage to start the venture.”
Arvel says patent discovery is a difficult problem to solve because it involves both a deep understanding of technology and the ability to compare different technologies in detail.
“That’s why it has been done almost entirely manually as long as the patent system exists. Even the most recent out-of-the-box machine learning models are too inaccurate to solve the problem. This is why we have developed a specific ML model for the patent domain that reflects the way human professionals search work and also makes the problem sensible for computers.
This approach is already being used by clients with IPRally, Spotify and ABB, as well as intellectual property offices. Target customers are described as any corporation that actively protects its own R&D with patents and has to navigate the IPR landscape of competitors.
Meanwhile, IPRally is not without its competition. Arvela cites industry giants like Clariat and Questale who dominate the market with traditional keyword search engines.
In addition, there are some other AI-based startups, such as Amplified and IPScreener. “IPRally’s graph approach makes searches more accurate, allows for detail-level computer analysis, and provides a non-black-box solution that is understandable and controllable by the user,” he says.