Embodied AI Workforce
Empowering heterogeneous platforms to deploy labor in the physical world
NeuxMind.AI follows a "decoupled hardware and software, operations-first" approach. Through Robot OS, it abstracts away the complexity of the underlying platform and standardizes the delivery of Super Agent's core intelligence to heterogeneous platforms. Rather than stacking hardware, NeuxMind.AI defines a unified "Intelligent Hub" for the physical world, enabling embodied AI workforces to be deployed and replicated at scale across industries in a standardized way.
Embodied Engineering Foundation:Plug-In Brain × Core Joint Modules
We do not build complete machines; we build only the most critical intelligent modules, giving any platform a "professional soul" through standardized interfaces.
Embodied Brain
A plug-and-play intelligence core integrating in-situ reasoning and pure-vision navigation
Integrating in-situ reasoning (edge closed loop) and pure-vision navigation, it is plug-and-play, works across multiple platform types without prebuilt maps or GPS, and uses visual perception to achieve autonomous navigation and decision-making in complex, dynamic environments.
Core Joint
A fully self-developed, high-precision drive architecture that combines lightweight design with industrial-grade reliability
A fully self-developed, high-precision drive architecture that balances lightweight design with strong power output, maintains precision under extreme loads and high-frequency motion cycles, supports rapid reconfiguration, and adapts to joint requirements across different embodied forms.
Data Acquisition & Training Center:The Next-Generation "Data Fuel Factory" for Embodied Intelligence
High-quality data is the foundational fuel for scaling embodied intelligence. The next-generation data acquisition and training center produces training data at lower cost and higher density, driving the continuous evolution of embodied AI Workers.
First-Person Multimodality
Using sensor devices such as glasses and gloves to simulate human data collection, it captures multimodal signals from the human perspective—including vision, touch, and motion—at higher efficiency and lower cost, building high-quality training datasets for embodied intelligence.
Hybrid Training Grounds
It builds a hybrid "field + training ground" data collection environment spanning real business scenarios such as retail, industrial production, and eldercare, allowing embodied AI Workers to undergo generalized training in diverse and demanding environments and achieve "ready for work on entry".