Arlequin AI raises €28M to build novel AI models that learn complex relationships at scale

Paris-based AI startup Arlequin AI SAS recently secured €28 million ($32 million) in Series A funding to develop novel AI models that can learn complex relationships at scale. The new architecture, based on topological neural networks (TNNs), differs from the graph-based neural networks found in most large language models. Arlequin has already built a scalable platform that can handle diverse data types, including documents, transactions, video, and operational information.

European investors, led by Redalpine and OTB Ventures with support from Bpifrance’s Defense Innovation Fund, co-led the round, while existing investors Vsquared Ventures and 10x Founders increased their stakes. Notable new backers include Xavier Niel and Zebox. The funding will help Arlequin scale its proprietary TNN model, which learns from data structures and relationships to capture complex, multipath interactions at large scale.

Co-founder and CEO Hugo Micheron emphasized the need for AI systems that can understand intricate dynamics within massive data sets as information overload continues. Micheron noted that Europe is competing with the U.S. and China to create powerful AI models. Arlequin's TNN architecture is designed to learn from individual data points and their connections, enabling the analysis of large systems and tracing end results back to root causes.

Potential applications include counterterrorism investigations, security and defense, criminal investigations, fraud detection, information integrity, cybersecurity, and AI safety and security. The startup also aims to reduce computational requirements for its TNN models, minimizing energy consumption, advanced hardware, and infrastructure costs.

Arlequin is collaborating with research teams at leading institutions, including the French National Institute for Research in Digital Science and Technology, the French National Center for Scientific Research, Max Planck Institute, and universities such as Oxford, Cornell, Princeton, and the University of California at Santa Barbara.

With the new funding, the company plans to expand its international team, accelerate commercial deployment across Europe and globally, and establish an AI lab in Silicon Valley.