Dyna raises $120M to advance Physical AI

  • September 23, 2025
  • William Payne

Physical AI developer Dyna Robotics has closed a $120 million Series A funding round. It was led by Robostrategy, CRV, and First Round Capital, with participation from Salesforce Ventures, NVIDIA’s venture capital arm NVentures, the Amazon Industrial Innovation Fund, Samsung Next, and LG Technology Ventures.

Dyna will use the latest funding round to expand its team, accelerate delivery of production-ready general purpose robots powered by proprietary embodied AI foundation models, and scale deployments across industries.

Since raising a $23.5 million seed round in March, Dyna’s progress has included launching its DYNA-1 model, a robotics foundation model that has increased the performance of robots to a 99+% success rate in 24 hours of non-stop operation.

Dyna has built a single-weight, general-purpose foundation model that can perform diverse daily tasks at commercial scale across varied environments. Its model has been deployed at multiple customer sites, supporting the model’s generalisation commercial viability and continuing to learn and improve rapidly from on-the-job experience.

“A strong foundation model is key to scalable distribution,” said Lindon Gao, co-founder and CEO of Dyna Robotics. “Our models continuously improve with each customer deployment, generating high-quality data. We are observing true generalisation as our robot enters new environments; it simply works out of the box, with no additional data.”

“Our first principle is to design robot foundation models that attain both generalisation and performance,” said co-founder Jason Ma, a former DeepMind research scientist who has focused his career on developing foundation models for robotics. “Scalable real-world robot learning systems need to master and generalise many manipulation skills. To achieve the best performance on complex tasks, Dyna’s foundation models are developed to enable general world understanding while learning from the models’ own experience for rapid online learning.”