
Unified AI Scheduling
AI algorithms dynamically allocate robot tasks and optimize routes across the hospital, coordinating device operations in real time to improve transport efficiency and response speed.
A full-loop ecosystem of Technology, Scenarios & Applications — putting intelligence to work in the real world.
A full-loop ecosystem of Technology, Scenarios & Applications — putting intelligence to work in the real world.


Hospital logistics face high labor costs, heavy non-clinical workloads for nurses, strict delivery deadlines before and after surgery, and the risk of cross-infection. An embodied AI model connects perception, decision-making and execution through hardware adapted to each scenario. Robots avoid obstacles, use elevators and carry supplies across floors, completing the full cycle of pickup, transport, handover and return. Remote operations and collected data support ongoing model improvement. Tasks include transporting contaminated linens and medical waste, routine ward patrols and information synchronization. Around-the-clock autonomous operation reduces non-clinical workloads by 30% and improves logistics efficiency by 50%, helping prevent cross-infection. The solution is already operating at the First People's Hospital of Kunshan.

AI algorithms dynamically allocate robot tasks and optimize routes across the hospital, coordinating device operations in real time to improve transport efficiency and response speed.

Full-process transport data is uploaded and backed up locally in real time, making records traceable, tamper-resistant and aligned with medical data security requirements.

A single-hospital deployment can start from RMB 100,000 without complex infrastructure changes, lowering the adoption barrier and enabling fast launch.

Perceives, decides and acts independently through a closed-loop workflow.

Adapts to dynamic environments and adjusts its strategy in real time to reach goals.

Improves through continuous data iteration and expands its capabilities over time.

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