RMB13.29 million! YIDU TECH (02158) wins bid for the First Affiliated Hospital of Chongqing Medical University's next-generation big data platform project, continuing to expand its medical data foundation layout in Grade 3A hospitals.

During today's midday trading session, YIDU TECH (02158) issued a voluntary announcement stating that its affiliate, Yidu Cloud (Beijing) Technology Co., Ltd., has won the bid for the First Affiliated Hospital of Chongqing Medical University's next-generation big data platform project, with a total project value of approximately RMB13.29 million. This bid win represents another business advancement for YIDU TECH in the field of data platform construction for large medical institutions. In recent years, YIDU TECH has continued to expand its business around medical data governance, clinical research, and medical AI applications, gradually forming a business layout spanning from data infrastructure to clinical intelligent applications, with related solutions deployed in 133 leading hospitals. As an important component of the digitalization of large medical institutions, hospital big data platforms undertake functions such as multi-source medical data integration, data standardization governance, and data resource utilization. As medical AI gradually extends into core scenarios including clinical diagnosis and treatment, research innovation, and hospital operations management, the focus of medical data infrastructure construction is also shifting from data aggregation to data quality improvement, business collaboration, and intelligent application expansion. High-quality, standardized medical data has become an important foundation for medical institutions to advance digital transformation and AI applications. Against the backdrop of the country's continued promotion of "AI + healthcare" development and strengthening of high-quality dataset construction in the health sector, YIDU TECH is accelerating its exploration of deep integration between AI and medical big data technologies. Just days ago, the company, together with Zhongda Hospital Southeast University, released high-quality data foundation achievements for medical world models at the 2026 Physical AI and World Models Conference, proposing a dual-track data system of "homologous complementarity, tiered services" that supports precise validation of specialty disease models and medical knowledge understanding and reasoning for large models through coordinated construction of structured task precision datasets and large model corpora, exploring a practical pathway for supporting the R&D and application deployment of medical world models with high-quality data foundations. In terms of clinical applications, YIDU TECH released "Xiao Huangqi," a TCM evidence-based intelligent agent under its Yidu Zhixun product line, at the 2026 World Conference on Traditional Medicine. This intelligent agent is designed for TCM clinical scenarios, providing doctors with intelligent evidence-based support covering functions such as TCM ancient text retrieval, TCM guideline literature tracing, auxiliary syndrome differentiation, Chinese herbal formula queries, and TCM terminology translation, supporting the inheritance and innovation, modernized clinical application, and international development of traditional Chinese medicine. The foundation of medical AI deployment lies in the data infrastructure. Big data platform projects at leading Grade 3A hospitals serve not only as a touchstone for service providers' technical capabilities, compliance systems, and delivery strength, but also as important testing grounds for cutting-edge medical AI technologies moving toward real clinical settings. Industry analysis suggests that this bid win further solidifies YIDU TECH's benchmark presence in Grade 3A hospitals in the southwestern region. As smart hospital construction continues to deepen, companies with both underlying data governance capabilities and multi-scenario AI product matrices are expected to continue unleashing growth potential, driving high-quality development of the healthcare industry through data elements.