As the wave of artificial intelligence sweeps across various industries, the healthcare sector, with its vast amounts of data, high barriers to entry, and specialization, is regarded as the most valuable yet challenging &#34;crown jewel&#34; for AI implementation. However, how to transform data into assets and convert AI technology into sustainable business revenue is a common challenge faced by global healthcare service companies.
In the United States, Tempus AI (TEM.US) has carved out a niche in the medical technology field through its unique &#34;data + AI&#34; model, becoming a darling of the capital markets, with its stock price reaching a high of $104.32 in October this year.
Meanwhile, with the continuous deepening of China's market-oriented mechanism for data elements, the exploration of the monetization of medical data is also steadily advancing. Against this backdrop, is there an opportunity for the next Tempus AI to emerge in the Chinese market? Which companies are likely to grow into representatives of Chinese medical AI with platform capabilities?
Zhitong Finance APP noted that recently, the leading Chinese medical imaging service company RIMAG GROUP (02522) released a data-related announcement. According to the announcement, in October 2025, RIMAG GROUP's subsidiary Beijing RIMAG Guanghe Information Technology Co., Ltd. (&#34;Beijing RIMAG&#34;) signed a &#34;Data Co-construction Cooperation Agreement&#34; with Beijing Data Pilot Zone Service Co., Ltd. (&#34;Beijing Pilot Zone&#34;) and Beijing International Computing Power Service Co., Ltd. (&#34;Beijing Computing Power&#34;). The cooperation will rely on a compliant regulatory framework of a data sandbox, based on the medical imaging data resources provided by Beijing RIMAG, with Beijing Pilot Zone responsible for data processing and compliance review, and Beijing Computing Power providing computing power and storage support. The three parties will jointly build a high-quality medical imaging dataset, conduct large model training, and explore innovative application scenarios for medical imaging data. By the end of October 2025, the medical imaging dataset co-built by the three parties successfully achieved its first commercial contract within the data sandbox.
The realization of this transaction reflects the gradual formation of a new cooperative model:
In the &#34;data sandbox&#34; built by state-owned assets, RIMAG GROUP, as a key provider of data services and technology, drives the entire value cycle and engages in &#34;value co-creation&#34; of data. This model not only attempts to address the fundamental challenges and key issues of data circulation but also provides a reference for exploring a development path for medical AI that is more in line with the characteristics of the Chinese market. It more clearly points to a future where RIMAG GROUP is highly likely to become a medical data intelligence giant cultivated in Chinese soil, with greater platform value and imaginative potential than Tempus AI.
<h2>Common Gene: Strategic Elevation from Medical Services to Data Platforms</h2>
Whether it is Tempus AI or RIMAG GROUP, their development trajectories reflect a strategic transformation from traditional medical services to data-driven platforms. The core business of both essentially constitutes a continuous, compliant, and high-quality source of data.
Tempus starts with genetic testing as an entry point, gradually integrating multi-source information such as clinical records, imaging data, and medication records, attempting to construct a &#34;digital twin&#34; of patients, with the goal of upgrading from a testing service provider to a data infrastructure provider in the life sciences field
The path of RIMAG GROUP is similar. By establishing and operating a network of third-party medical imaging centers in China, the company delves into the forefront of medical data generation, forming a virtuous interaction between business development and data accumulation.
For investors, this &#34;core business as data source&#34; model has dual appeal. First, it ensures the authenticity, continuity, and scalability of data, which is a prerequisite for training reliable AI models. Second, the revenue from the core business provides stable cash flow support for expensive data governance and AI output work, avoiding the financial risks of pure AI startups &#34;burning money&#34; on R&amp;D.
<h2>Deepening Data Value: The Anchoring Role and Multidimensional Expansion Potential of Imaging Data</h2>
Having data resources is just the starting point; how to transform them into high-value, tradable data products is key to building competitive barriers. In this process, the unique value of medical imaging data deserves in-depth exploration.
Medical imaging data has a natural &#34;anchoring&#34; role in personal medical information. Compared to the common issues of information loss and unstructured data in clinical text data, imaging data—especially in the management of diseases like tumors that require long-term follow-up—can provide objective, quantifiable information such as lesion location, size, and age, offering a stable and reliable reference benchmark for clinical decision-making.
RIMAG GROUP has already made certain accumulations in the standardization and refinement of imaging data. For example, the company initiated the formulation of the &#34;Standards for Medical Imaging Examination Project Names and Coding&#34; early on, promoting the standardization and unification of internal data, laying the foundation for subsequent data circulation and platform application. At the same time, leveraging its imaging center network and professional physician resources, the company has established multi-level quality control and annotation processes, gradually forming high-quality, reusable annotated datasets.
Through the combined driving model of &#34;standardized coding + refined annotation,&#34; RIMAG GROUP has developed its own characteristics in terms of data quality and usability. This model has certain comparability to the barriers established by Tempus in the United States, but there are differences in the paths to realization and applicable scenarios.
It is noteworthy that RIMAG GROUP has not stopped at imaging data and is extending from imaging data to multidimensional data. The company anticipates that the implementation of the Tianjin Beichen project is promoting its evolution from a single imaging data service to a comprehensive platform integrating imaging, pathology, laboratory tests (including genetics), health check-ups, and electrophysiology. This project encompasses five major modules: regional imaging sharing center, smart integrated laboratory, digital pathology center, health management center, and nuclear medicine center. This multimodal data integration practice provides new possibilities for the deep value excavation of medical data.
As the project progresses, if RIMAG GROUP can establish China's first large-scale, standardized, multimodal medical dataset, it may provide more possibilities for the company's business development and could also serve as a reference for improving the industry's data application level. From imaging data to multidimensional integration, the development path of medical data is continuously expanding, and the value space is being redefined, while RIMAG GROUP has already gained a first-mover advantage in this trend through the &#34;Beichen model.&#34;
<h2>Ecosystem Construction vs. Vertical Integration: Financial Mirror Analysis of the Business Model of Medical Data Platforms</h2>
After the initial formation of data capabilities, RIMAG GROUP and Tempus AI show significant differences in their commercialization paths.
Tempus AI tends to favor vertical integration, focusing on serving B-end clients such as pharmaceutical companies and insurance institutions, providing data authorization, analytical services, and SaaS solutions to support drug research and precision medicine.
On the other hand, RIMAG GROUP places greater emphasis on ecosystem construction, aiming to create a closed loop of &#34;data-model-scenario.&#34; On one hand, it provides high-quality data products through channels such as data exchanges to serve AI research and development companies and research institutions; on the other hand, it participates in building data sandboxes in regional pilot projects like the &#34;Yizhuang model,&#34; supporting compliant data collaboration. Additionally, the company is exploring the application of imaging data and AI capabilities in various scenarios such as enhancing grassroots medical care, evaluating clinical trials for pharmaceutical companies, and analyzing the efficacy of medical devices.
This path difference is also reflected in their financial structures. Tempus's revenue is still primarily from laboratory services, while revenue from its technology platform is gradually growing; RIMAG GROUP, however, shows a &#34;three-tier evolution&#34; trend: the first tier is still based on medical imaging center services, the second tier, a high-growth engine, is data empowerment and service revenue (including data trading and technology platform services). With the successful trading of its datasets on the data exchange and the operationalization of the &#34;data sandbox&#34; model, this business line is transitioning from an exploratory &#34;model validation&#34; phase to a scalable &#34;value realization&#34; phase. This is a key moment for a qualitative change in its valuation logic. The third tier's potential lies in AI software and model licensing revenue, which, as its large models mature, will open up greater monetization opportunities through SaaS subscriptions and pay-per-case models.
According to Zhitong Finance APP, from a business model perspective, RIMAG GROUP's path leans more towards the positioning of an &#34;ecosystem builder.&#34; It is not satisfied with merely being a part of the industrial chain but aims to become the core hub of the entire medical imaging AI ecosystem by empowering upstream and downstream players. The advantage of this model lies in its growth being deeply tied to the overall growth of China's medical AI industry, enjoying both the beta returns of the entire track and the alpha returns of the platform.
Notably, on October 30, RIMAG GROUP announced a nearly 100 million yuan capital increase in its incubated core AI enterprise, Shanghai Yinghe Yimai Intelligent Technology Co., Ltd., further increasing its shareholding ratio.
As a key AI enterprise incubated by RIMAG GROUP, Yinghe Yimai's core business covers the operation of an intelligent service platform for the entire process of medical imaging, AI-assisted diagnostic technology, and digital imaging solutions. Its capabilities in technology research and development and product implementation are highly complementary to RIMAG GROUP's existing imaging service ecosystem. The characteristics of &#34;ecological complementarity and resource interconnection&#34; lay the foundation for deep collaboration between the two parties and have become a key consideration for RIMAG GROUP's increased investment.
The long-term value of this investment lies not only in strengthening the company's strategic layout in AI technology research and development and product implementation but also in achieving an organic connection of &#34;multi-dimensional data + AI layout + data trading&#34; in business logic, thereby solidifying the company's industry ecological barriers.
<h2>Outlook: Development Path and Value Considerations of Data Intelligence Platforms</h2>
RIMAG GROUP's recent investment in AI technologies such as medical imaging large models reflects its intention to promote the transformation of data value into intelligent applications. Based on large models, the company is expected to develop specialized AI applications at lower costs and higher efficiency, gradually building a model ecosystem for developers.
Its core logic lies in constructing a &#34;data-model-scenario&#34; closed loop: starting with imaging networks and data governance capabilities to create high-quality data products; driving value release through large models; and mature models feeding back into business efficiency improvements. If this closed loop can continue to operate, it will form a self-reinforcing development cycle, becoming the company's long-term competitive advantage.
From an industry perspective, in the wave of data factorization and AI intelligence convergence, the &#34;state-owned asset guarantee, data-driven, ecosystem co-construction&#34; model practiced by RIMAG GROUP provides another possibility for the development of Chinese medical data enterprises. Its value is not only reflected in the single-point capabilities of technology or data but also in whether it can form a cross-scenario, sustainable intelligent ecosystem. This also means that the market's valuation of it needs to be comprehensively considered in conjunction with the development characteristics of a higher-dimensional &#34;data intelligence platform ecosystem.&#34;

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Against the backdrop of the intersection of medical data and AI, RIMAG GROUP promotes the development of Chinese medical data enterprises through the model of "state-owned asset guarantee, data-driven, and ecological co-construction." The successful model of Tempus AI in the United States provides a reference for the Chinese market. Recently, RIMAG GROUP signed a cooperation agreement with the Beijing Data Pilot Zone and Beijing International Computing Power Service Company to jointly build a medical imaging dataset and explore innovative application scenarios, marking the formation of a new cooperation model

Decoding the core logic of medical data and AI, can RIMAG GROUP tell a good story about China's Tempus AI?