Taiwan's healthcare system is undergoing a fundamental shift: hospitals are moving from using individual AI tools to deploying coordinated teams of AI agents that reason, plan, and act across clinical workflows. Foxconn, the electronics manufacturing giant, is leading this transformation by integrating NVIDIA's NemoClaw agent framework into its CoDoctor AI platform, which now powers specialized agents across Taiwan's major medical centers.

What Makes AI Agents Different From Traditional Healthcare AI?

The distinction matters because hospitals operate as complex systems where no single AI tool can keep pace with the constant coordination required. Traditional AI systems excel at specific tasks,reading an EKG, detecting cancer in imaging, or flagging abnormalities. But they don't communicate with each other or adapt to the unpredictable flow of a hospital floor. AI agents, by contrast, are always-on systems that reason through problems, coordinate with other agents, and adjust their actions in real time.

Foxconn's approach divides these agents into two categories: digital agents that operate inside hospital systems, handling clinical reasoning and documentation, and physical agents like robots that move through hospital spaces, managing logistics and procedural support. This dual-layer architecture allows hospitals to extend their clinical workforce capacity without simply adding more staff.

How Are Hospitals Deploying These AI Agent Teams?

• Cardiovascular Screening: An ECG AI agent helps hospitals triage cardiac patients more efficiently, while a Corovia AI agent reconstructs the heart and coronary arteries in 3D, reducing a two-hour clinical workflow to just one minute.
• Cancer and Diagnostic Support: Specialized agents handle breast cancer screening, fundus imaging for eye disease, and colonoscopy procedures with real-time lesion detection at millisecond-level speeds.
• Surgical Assistance: Foxconn's Scrub Bot, an AI-enhanced collaborative robot, operates in live surgical suites, responding to surgeon voice commands and adapting in real time to changing surgical needs.
• Nursing and Logistics: The Nurabot nursing robot, powered by NVIDIA's physical AI stack, handles transport and logistics tasks, freeing an estimated two to three hours per day for nurses to focus on direct patient care.

These agents are built on NVIDIA NemoClaw, an open-source framework for constructing agentic orchestration layers that coordinate multiple specialized systems. Foxconn's CoDoClaw platform, built on NemoClaw, advances CoDoctor from standalone AI tools into a multi-agent system capable of coordinating across breast cancer screening, ECG analysis, fundus imaging, and coronary artery analysis through a unified clinical interface.

Why Is Taiwan Investing $1.5 Billion in This Approach?

Taiwan faces one of the world's fastest-aging populations, creating mounting pressure on its clinical workforce. The government's "Healthy Taiwan" initiative, backed by a $1.5 billion regional investment, treats agentic AI as a new hospital operating system designed to scale clinical expertise and extend workforce capacity to serve the population's growing demands.

The results so far suggest the strategy is working. Taiwan's medical centers now operate mature AI systems in their daily workflows, with a majority of the country's major hospitals engaged in AI research or clinical trials. These active deployments span institutions including Chang Gung Memorial Hospital, National Taiwan University Hospital, Taichung Veterans General Hospital, and Taipei Veterans General Hospital, collectively handling more than 14 million patient encounters annually.

"The next era of healthcare is being powered by agentic AI,teams of digital and physical AI agents working alongside clinicians," said Kimberly Powell, vice president of healthcare at NVIDIA. "Together with Foxconn and Taiwan's leading medical centers, NVIDIA is accelerating the deployment of AI infrastructure that helps clinical teams, improves hospital efficiency and creates a model for health systems around the world."

Kimberly Powell, Vice President of Healthcare at NVIDIA

What Role Does Simulation Play in Safe Deployment?

Before robots and agents enter real clinical settings, Foxconn builds NVIDIA Omniverse-powered digital twins of hospital facilities. These virtual replicas allow AI and robotic systems to be tested, trained, and validated in a risk-free environment before deployment. This simulation-first approach has cut deployment time by 40 percent and enabled 98 percent navigation accuracy, creating a safer and faster path from development to actual patient care.

The Nurabot nursing robot exemplifies this approach. After completing field validation at Taichung Veterans General Hospital last year, it has moved beyond the pilot phase toward broader multisite deployment, now being gradually introduced into additional hospitals including Taipei Veterans General Hospital and Tungs' Taichung MetroHarbor Hospital, as well as long-term care settings and overseas nursing education institutions.

What Does This Mean for Healthcare Systems Elsewhere?

Taiwan's model is significant because it demonstrates how a strong commitment to AI-native healthcare can move from vision to measurable reality. With 85 FDA- or TFDA-cleared medical AI solutions already in use, Taiwan is proving that agentic AI isn't theoretical; it's operational at scale. The country's experience suggests that healthcare systems facing similar challenges,aging populations, clinician shortages, and rising costs,have a proven blueprint to follow.

Foxconn's role as ecosystem integrator is equally important. By connecting government programs, hospitals, device makers, and software companies, Foxconn is demonstrating how a single organization can accelerate the deployment of real-world clinical AI at scale, rather than leaving hospitals to piece together disparate tools and vendors.

"Foxconn is building the AI infrastructure and clinical platforms to connect hospitals, medical devices and software innovators across Taiwan," stated Barry Chiang, president of B group and Digital Health at Foxconn. "With NVIDIA technologies across accelerated computing, simulation, edge AI and robotics, we are helping healthcare providers move from proof of concept to scalable, safe deployments that can improve care delivery."

Barry Chiang, President of B Group and Digital Health at Foxconn

The shift from individual AI tools to coordinated agent workforces represents a maturation of healthcare AI. Rather than asking "Can AI do this task?" hospitals are now asking "How can multiple AI agents work together to improve the entire patient journey?" Taiwan's healthcare system is answering that question in real time, with results that other aging societies are watching closely.