IPRally builds a knowledge graph-based patent search engine powered by an explainable AI graph neural network trained on millions of real patents to capture technical and semantic relationships beyond keyword matching. The platform emphasizes explainability, allowing users to see why results were returned and to better understand relevant prior art. IPRally positions itself as a modern alternative to legacy IP tools in the billion-dollar IP management market dominated by incumbents like Clarivate, Anaqua and Questel. The company has attracted customers including Nvidia, Dolby and Bentley. With the new funding, IPRally plans to expand beyond patent search and categorization toward a more comprehensive patent insights platform. Financially, the startup raised €10 million ($10.8 million) in a Series A, following an earlier €2.4 million seed tranche. IPRally has developed a knowledge graph-based search engine and domain-specific ML model to make patent search more accurate and explainable than keyword or black-box approaches. The startup’s graph approach aims to distill patent publications into machine-readable representations that mirror how IP professionals think. Co-founded by CEO Sakari Arvela (15 years as a patent attorney) and CTO Juho Kallio, the team says the method enables detailed, explainable comparisons of technologies. Customers include Spotify, ABB and intellectual property offices; target users are corporations that actively protect R&D with patents. IPRally faces incumbents such as Clarivate and Questel and AI competitors like Amplified and IPScreener. Financially, the company has raised €2.35 million to date, including the recent €2 million seed round.

Total raised

$13M

Funding rounds

2

Latest round

Series A

Latest activity

Mar 2023