The rollout includes clinical agents, surgical robots and digital twins for testing workflows before hospital use.
NVIDIA has announced that Foxconn and several medical centers in Taiwan are deploying AI systems based on NVIDIA technology as part of the region’s shift toward more AI-supported healthcare operations.
Taiwan has one of the world’s fastest-aging populations, increasing pressure on clinical staff. Managing care across clinicians, devices, treatment rooms and shift schedules remains complex, and hospital workflows often involve multiple disconnected systems.
Agentic AI is being positioned as a way to support hospital operations by coordinating clinical and operational tasks and extending workforce capacity. In this model, AI systems are used to help manage growing care demands across healthcare settings.
Specialized agents are AI systems designed for specific domains and intended to operate continuously across clinical and operational workflows in digital and physical environments. Digital agents work inside software systems to support clinical reasoning, documentation and care coordination, while physical agents such as robots and connected devices are used for logistics, monitoring and procedural support in hospital settings.
Under Taiwan’s Healthy Taiwan initiative, the region has committed $1.5 billion to build a regulated health AI ecosystem involving hospitals, academic institutions and technology companies. Foxconn is acting as an integrator among government programs, hospitals, device manufacturers and software providers to support deployment of clinical AI systems.
AI tools for clinical support
Foxconn’s CoDoctor platform is designed as a coordinated set of specialized AI agents for areas including cardiovascular care, oncology and ophthalmology. The platform is intended to help clinicians with diagnosis support, documentation and coordination across departments.
The current CoDoctor AI tools include an ECG AI agent for EKG-based screening and triage, a Corovia AI agent that reconstructs the heart and coronary arteries in 3D to shorten parts of the clinical workflow and an Endovia AI agent for colonoscopy that supports real-time lesion detection and low-latency AI-assisted workflows.
Foxconn’s clinical AI platform uses NVIDIA Nemotron open models for clinical reasoning and multimodal processing. These models use open weights, allowing healthcare organizations to manage and adapt them within their own environments.
Foxconn also introduced CoDoClaw, a clinical agent system built on NVIDIA NeMoClaw, an open-source blueprint for autonomous agent deployment, and NVIDIA OpenShell for privacy and security controls. CoDoClaw is intended to connect multiple AI tools through one clinical interface, including systems for breast cancer screening, ECG analysis, fundus imaging and coronary artery analysis.
These AI systems are being deployed at medical centers in Taiwan for uses such as ECG screening, cancer subtype classification, surgical planning and real-time support during procedures including colonoscopy.
Physical AI systems in hospitals
AI-based systems are also being used in physical hospital environments, where they operate alongside clinicians and other digital systems in wards and operating rooms.
Foxconn introduced Scrub Bot, a collaborative robot designed for surgical suites. It is intended to respond to voice commands from surgeons and adjust to changing requirements during procedures.
NVIDIA also introduced the Agent-Ready Rheo blueprint within NVIDIA Isaac for Healthcare to support development of hospital automation workflows. Foxconn is using Rheo for simulation-to-real workflows including scene reconstruction, policy training, evaluation and deployment.
Foxconn’s Nurabot, a nursing robot built on NVIDIA’s physical AI stack, completed field validation last year at Taichung Veterans General Hospital and is now moving into broader deployment. Additional rollout is under way at Taipei Veterans General Hospital, Tungs’ Taichung MetroHarbor Hospital, long-term care settings and nursing education institutions outside Taiwan.
Foxconn estimates that Nurabot can reduce the time nurses spend on transport and logistics tasks by two to three hours per day, allowing more time for direct patient care. Future Nurabot deployments are also being tested with NVIDIA NeMoClaw and physical AI technologies to support more coordinated clinical workflows and simulation-based development.
To prepare robots for hospital use, Foxconn creates digital twins of hospital facilities using NVIDIA Omniverse. These virtual models are used to test, train and validate robotic and AI systems before deployment in clinical environments. Foxconn reports that this approach has reduced deployment time by 40% and enabled navigation accuracy of 98%.
Taiwan’s healthcare AI deployment model
Taiwan currently has 85 FDA- or TFDA-cleared medical AI solutions, and major medical centers in the region are involved in AI research or clinical trials. This reflects a broad effort to incorporate AI tools into healthcare delivery.
Many medical centers in Taiwan now use AI systems in routine workflows. Deployments are active at Chang Gung Memorial Hospital, Kaohsiung Medical University Chung-Ho Memorial Hospital, MacKay Memorial Hospital, National Taiwan University Hospital, Taichung Veterans General Hospital, Taipei Veterans General Hospital and other healthcare sites that together handle more than 14 million patient encounters each year.
These projects present Healthy Taiwan as one model for countries seeking to build regulated national healthcare AI systems using NVIDIA-based infrastructure.
For more information, visit nvidia.com.
