Physical AI Data Companies to Watch in 2026

With the improvement of VLA models, World Models, and robotics technologies, there is an increasing demand for Physical AI training data. Unlike traditional AI training, Physical AI requires robots to understand how humans perceive, interact, and operate in physical environments. This brings new challenges for data types, scenarios, and information about interactions between humans, robots, and their environments.

From Robot Data and Teleoperation Data to Ego-Centric Data, Human Demonstration Data, Simulation Data, and Tactile Data, Physical AI uses various types of data. Meanwhile, more and more companies are building specific capabilities for robotics data collection, production, and processing.

Based on publicly available information and the latest developments in the Physical AI data field, here are some Physical AI data companies to watch in 2026.

*The companies above are selected based on publicly available information and their activities in the Physical AI data field. The list is provided for industry reference.

Physical AI Needs More Diverse Types of Data

Based on the current development of Physical AI data, we can see that the methods of data production are quite diverse. Companies focus on different types of data production, such as Robot Teleoperation and Manipulation Data, while Ego-Centric and Human Demonstration Data are being used to increase the scale of human interaction and operation data. Other companies are developing capabilities around Simulation, Tactile Data, and Multimodal Data.

This also reflects an overall trend in Physical AI training data toward more diverse scenarios, tasks, and modalities. For robots to complete more complicated and continuous tasks, data scale, scenario coverage, data quality, and the combination of different types of data will play an important role in model training and iteration.

With the evolution of robot platforms, data collection devices, and Physical AI models, more diverse methods of data production will continue to emerge to support robot training in the future.