
Zurich-based Flexion, a robotics intelligence startup building a reinforcement learning platform for humanoid robots, has raised €43 million ($50 million) in Series A funding.
SUMMARY
- Zurich-based Flexion, a robotics intelligence startup building a reinforcement learning platform for humanoid robots, has raised €43 million ($50 million) in Series A funding.
The round was led by DST Global Partners, with participation from NVentures (NVIDIA’s venture arm), redalpine, Prosus Ventures, and Moonfire. This follows a €6.3 million ($7.35 million) Seed round closed just months earlier.
“Our mission is simple but ambitious: to power the intelligence stack for humanoid robots, so they can work alongside humans, not depend on them. We’re not building the body. We’re building the brain. This is a hard problem. But the right kind of hard,” said the Flexion team.
Across Europe, 2025 has brought a steady stream of investment into robotics and autonomous systems. Notable raises include Germany’s NEURA Robotics (€120M for its cognitive humanoid platform), Unchained Robotics (€8.5M to scale its automation-matching software), and sensmore (€6.5M for “Physical AI” in heavy machinery.
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Additional funding rounds include Energy Robotics (€11.5M for autonomous inspection), Greece’s Progressive Robotics (€1.55M for no-code automation), Italy’s Adaptronics (€3.15M for adaptive grippers) and Switzerland’s mimic (€13.8M for dexterous robotic hands).
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Together, these deals total roughly €165M in disclosed funding, placing Flexion’s €43M Series A among the year’s more significant mid-sized raises, amid broad investment across cognitive robotics, autonomous inspection, dexterous manipulation, and industrial automation.
Founded in 2024, Flexion aims to build the intelligence layer for robotics focusing not on hardware but on the adaptive autonomy needed to make humanoid robots functional in dynamic real-world environments. Its founding team brings expertise in reinforcement learning, control systems, mechatronics, and perception, with backgrounds at ETH Zurich, NVIDIA, Meta, Google, Tesla and Amazon.
Flexion’s platform integrates natural-language task understanding, synthetic vision-language-action training, and transformer-based full-body control, enabling robots to act with minimal human supervision and move beyond pre-scripted or teleoperated behaviours.
The new funding will expand R&D in Zurich, increase compute and robotics infrastructure, establish a U.S. presence, and accelerate commercial deployment of its autonomy stack. Flexion is already working with major OEM partners, and the additional capital will help deepen and globalise these collaborations.
While many robotics firms focus on lifelike humanoid designs, few have achieved scalable utility beyond the lab. Flexion targets the core bottleneck robot cognition by decoupling intelligence from hardware.
Its platform is designed to operate across diverse robot morphologies, unlocking applications in manufacturing, logistics, industrial automation, disaster response and potentially extraterrestrial missions.
As demographic shifts intensify and labour shortages deepen particularly in industrial production Flexion views humanoid robotics not merely as a technological breakthrough, but as an economic imperative.
With one-third of the developed world expected to be over 60 by 2050 and productivity demands rising, adaptable autonomous systems are becoming essential to sustaining global industries.
Powered by the convergence of LLM-scale compute and next-generation simulation environments, Flexion is positioned to redefine how robots move, perceive, and reason in the real world.
About Flexion Robotics
Flexion Robotics develops advanced autonomy for humanoid robots enabling them to perform everyday human tasks with precision and adaptability. Its platform delivers a full intelligence stack from command and control to manipulation and locomotion designed to work across any hardware. Using simulation and reinforcement learning, Flexion scales real-world robot performance with minimal human input.







