From foundational algorithms to embedded engineering deployment, Motovis develops everything in-house with no technology gaps, ensuring deep software–hardware synergy. Backed by five international algorithm competition titles, our solutions adapt to mainstream global chip platforms and deliver highly reliable, low-latency mass production at scale, meeting automakers' diverse requirements.
Motovis builds on the World Model and VLA (Vision-Language-Action) architecture. The World Model learns the dynamics of the physical world, generating high-fidelity driving scenarios and driving-behavior data across diverse weather conditions and day–night cycles to provide scalable training support for long-tail scenarios. The One-Stage End-to-End architecture internalizes the World Model, unifying perception, prediction and decision-making through camera-only input to anticipate complex traffic interactions.
Motovis's proprietary Magic Wheel data platform connects global fleets 24/7. Shadow mode automatically captures high-value scenarios; cloud-based foundation models perform auto-labeling and data mining with a hundredfold gain in processing efficiency. From real-world feedback to model upgrade in as little as seven days, the complete closed loop — spanning algorithm development and testing through OTA updates — helps customers shorten development cycles.