As artificial intelligence sweeps across industries, the healthcare sector—with its vast data, high barriers, and specialization—is regarded as the "crown jewel" for AI implementation, offering both immense value and challenges. However, transforming data into assets and AI technology into sustainable commercial revenue remains a global challenge for healthcare service providers. In the U.S., Tempus AI (TEM) has emerged as a leader in medical technology with its unique "data + AI" model, becoming a darling of capital markets with its stock price peaking at $104.32 in October this year. Meanwhile, as China's data element marketization mechanism deepens, the exploration of medical data monetization is steadily advancing. Against this backdrop, could China produce its own Tempus AI? Which companies have the potential to become China's leading medical AI platforms?

RIMAG GROUP (02522), a leader in China's medical imaging services, recently announced a data-related collaboration. In October 2025, its subsidiary, Beijing RIMAG Information Technology, partnered with Beijing Data Pilot Zone Service Co. and Beijing International Computing Service Co. to sign a Data Co-Construction Agreement. Under this agreement, RIMAG will provide medical imaging data resources, while the partners will handle data processing, compliance review, and computing/storage support. Together, they aim to build a high-quality medical imaging dataset for large-scale model training and explore innovative applications. By late October 2025, the dataset achieved its first commercial contract within a domestic "data sandbox," reflecting a new collaborative model where RIMAG serves as the key data and technology provider, driving value creation within a state-backed regulatory framework.

Both Tempus AI and RIMAG GROUP share a strategic evolution from traditional medical services to data-driven platforms. Tempus AI started with genetic testing and expanded into integrating clinical records, imaging, and medication data to create "digital twins" of patients, positioning itself as a data infrastructure provider in life sciences. Similarly, RIMAG has built a network of third-party medical imaging centers in China, embedding itself at the forefront of medical data generation. This "business-as-data-source" model offers dual appeal: ensuring data authenticity, continuity, and scale for reliable AI training while leveraging steady cash flow from core operations to support costly data governance and AI development.

Medical imaging data holds unique value as an "anchor" in personal health information, providing objective, quantifiable insights for diseases like cancer. RIMAG has made strides in standardizing and refining such data, establishing quality control and annotation processes to create reusable datasets. Beyond imaging, the company is expanding into multi-dimensional data integration, as seen in its Tianjin Beichen project, which combines imaging, pathology, lab tests (including genetics), and electrophysiology. This multi-modal approach could position RIMAG as China’s first large-scale, standardized medical data platform.

While Tempus AI focuses on vertical integration—serving pharmaceutical and insurance clients with data licensing and SaaS solutions—RIMAG prioritizes ecosystem building. It aims to close the loop between data, models, and applications, supplying data products via exchanges, participating in regulatory sandboxes, and exploring AI applications in primary care, clinical trials, and medical device analysis. Financially, RIMAG’s three-tiered growth model—anchored by imaging services, accelerated by data monetization, and fueled by future AI software licensing—signals an impending valuation shift.

In late October, RIMAG announced a nearly 100 million yuan investment in Shanghai Yinghe Yimai Intelligence Technology, a key AI subsidiary specializing in intelligent medical imaging platforms and diagnostic solutions. This move strengthens RIMAG’s AI capabilities and aligns with its strategy to integrate multi-dimensional data, AI deployment, and data transactions, reinforcing its ecosystem moat.

Looking ahead, RIMAG’s investments in medical imaging AI models reflect its push to convert data into intelligent applications. By developing low-cost, high-efficiency specialized AI tools and fostering a developer ecosystem, the company seeks to create a self-reinforcing "data-model-scenario" cycle. As China’s data and AI waves converge, RIMAG’s state-backed, data-driven, ecosystem-oriented model offers a distinct path for medical data firms. Its valuation hinges not just on standalone capabilities but on its potential to build a cross-scenario, sustainable intelligent ecosystem—a metric demanding higher-dimensional assessment.