Winner of the “AI Pioneers” award (France 2030), Bleu Robotics is bridging the gap between academic research and industrial reality. Co-founded by INRIA researchers Serena Ivaldi and Jean-Baptiste Mouret alongside industrial expert Benoît Berkoukchi, the startup builds on 20 years of research in humanoid robotics and AI, to finally deliver AI-powered humanoid robots to industry.

Bleu Robotics raises €5M to scale humanoid robot deployment. Published: 29 October 2026 Les cofondateurs de Bleu Robotics, Benoit Berkoukchi, CEO, Jean-Baptiste Mouret, CTO et Serena Ivaldi, directrice du board scientifique, prennent la pose dans leurs locaux. Paris, France. 9 octobre 2026. Bleu Robotics, a startup developing AI models for industrial humanoid robots, has raised a €5 million pre-seed round, co-led by Contrarian Ventures and OVNI Capital, with participation from Kvanted, WEPA Ventures, Motier Ventures and Charlie Songhurst, technology investor and board member at Meta The company plans to utilise the funds to grow its team and scale its software solution across industries, pursuing its goal of reducing the full humanoid robot deployment process to one hour or less. Five million industrial robots were operating globally in 2025, according to the International Federation of Robotics. These robots are designed to repeat fixed tasks and cannot adapt to the high-mix, low-volume production now common in modern manufacturing, so human workers still do much of the work. Humanoid robots help to automate a wider range of complex tasks. While hardware has advanced in recent years, software development has struggled to keep pace, limiting real-world deployment. Interact Analysis found that out of the 20,000+ humanoids produced last year, only 10% reached real-world applications. Currently, most robots rely on end-to-end models that learn everything in a single black box and require massive amounts of data to achieve production-ready reliability. As a result, deployment is costly and time-consuming for manufacturers, often requiring hundreds of hours of training data, with no guarantee the robot will perform reliably. Bleu's technology removes the need for those large task-specific datasets and long training cycles, enabling manufacturers to deploy robots cost-effectively and at scale. Bleu Robotic's abductive learning model lets the robot learn a new task from as few as ten operator demonstrations, while maintaining the explainability required for industrial safety and the 99%+ accuracy production lines demand. The model eliminates the need for large amounts of training data by inferring the most likely intent behind an operator's demonstration, including the task's goal and constraints, and determining how to reproduce it reliably. The software can be plugged into any humanoid platform. Operators can teach it new tasks at the workstation using Bleu's training devices and handheld grippers that eliminate the need for coding, and can retrain the same robot as production needs change or move it to another site. Benoît Berkoukchi, co-founder of Bleu Robotics, said, "Humanoid robots in manufacturing are the next automotive sector, with the potential to help Europe and the US reshore production. But most robotics companies are trying to train humanoids with millions of data points and build fully general-purpose models. That approach isn't suited to manufacturing. There isn't enough data on factory work, and there won't be internet-scale data, the kind LLMs were built on, for robots for a long time. Our methodology means we can do more with less." Thomas Poitrineau, investor at Contrarian Ventures, said, "We were attracted to Bleu Robotics because of their ambitious choice to rethink how humanoid robotics software should work from first principles. It's rare to find a company led by two world-class robotics researchers and a manufacturing expert, which is also why their software works differently from their competition. Their goal is far bigger than simply making the best model in a lab. It's an approach that can already scale, putting robots to work in factories within months rather than years."