Perceptron develops vision and embodied-AI models for robots and other physical systems. Its model stack combines video understanding, spatial grounding, task-progress reasoning and robot control, with open Isaac releases and a commercial perceptive-language API.
About
Perceptron builds multimodal models that connect visual understanding with action in physical environments. Its Isaac family targets embodied reasoning and robot control, while Perceptron Mk1 and the company API support grounded detection, localisation, OCR and visual question answering across video and images. The software is aimed at robotics, manufacturing, logistics, security and other systems that need structured perception outputs.
Isaac 0.5 is a 36-billion-parameter sparse model trained across more than 35 robot systems, 100,000 hours of robot experience and one million hours of general video. Perceptron released model weights, training and inference code, and a technical report in August 2026. The model accepts images, video, language, robot state and prior actions, and can produce grounded visual outputs or robot actions.