On the afternoon of April 24, the roadshow area at the 2026 China Hospital Information Network Association (CHIMA) conference was packed with attendees, with even the aisles filled. Many held up their phones throughout the event, not wanting to miss a key moment. This was the scene at the launch of YIDU TECH's "Medical Agent Development and Collaborative Application Solution." After two years of intense competition focused on model parameters in the medical large model sector, the industry has finally witnessed a release that genuinely addresses the practical needs of hospitals and doctors. On this day, YIDU TECH announced a comprehensive upgrade in its product strategy through a multi-faceted approach: shifting from providing hospitals with intelligent tools to building open, evolvable agent development and collaboration systems. The enthusiastic response reflects the urgent demand among medical professionals and administrators for AI solutions that are practical and reliable.
The core challenge lies in the proliferation of medical AI that hospitals struggle to effectively utilize. Over the past two years, large models have rapidly impacted various industries, with the medical field becoming a key battleground. However, behind the frequent product launches, an awkward reality has emerged: large models often face compatibility issues in hospital settings due to inconsistent data standards, reluctance in clinical application, and limitations in handling complex medical conditions. The industry is undergoing a fundamental shift where AI must not only be usable but also reliable, practical, and indispensable. Application standards for medical AI must evolve from basic technical feasibility to clinical necessity.
The actual challenges extend further. During this year's National People's Congress sessions, committee member Huo Yong highlighted three major shortcomings: data silos hindering model iteration, concerns about reliability and usability, and insufficient coverage of out-of-hospital health services. Medical data's multimodal nature, high complexity, and stringent compliance requirements make it difficult for general large models to function effectively in critical healthcare scenarios. Establishing a competitive edge in medical AI requires more than advanced algorithms; it demands solutions for data governance, knowledge structuring, and scenario engineering.
The digital transformation of healthcare is essentially about modeling and optimizing complex systems, noted an industry expert at the roadshow. This requires both a systematic framework and a divide-and-conquer approach, working with top-tier hospitals and expert teams to build the AI hospital of the future—not as a one-time project but as an ongoing process of integration and evolution.
YIDU TECH's release addresses this core challenge by enabling AI to grow naturally within hospital environments. The solution centers on AI Middle Platform 3.0 as the foundation for hospital-wide AI capabilities, providing standardized, manageable production and operational support for IT departments. Clinical Assistant Copilot 2.0 serves as the primary interface for doctors, deeply integrated into daily diagnostic workflows, while the clinical version of Yidu Smart Loop delivers evidence-based knowledge. These three components work in synergy: the middle platform supplies capabilities, Copilot handles scenarios, and Yidu Smart Loop provides knowledge, forming a complete intelligent system where knowledge empowers scenarios and scenarios activate knowledge.
AI Middle Platform 3.0 fully supports the Model Context Protocol (MCP) and Skill frameworks, introducing AI-assisted workflow orchestration and enabling natural language definition of agents and tool integration, significantly lowering development barriers. Hospitals can now develop their own clinical agents and accumulate specialized assets. Clinical Assistant Copilot 2.0 features an intelligent scheduling engine that matches and activates hundreds of disease-specific agents based on doctors' natural language commands, shifting from tool-seeking to AI-driven assistance. The new "Quick Note" function uses OCR to extract external medical data, generating comprehensive patient profiles with one click. Integrated with Yidu Smart Loop, it automatically reads patient data to produce personalized, traceable treatment recommendations.
Underpinning these advancements is YiduCore, YIDU TECH's core algorithm engine. By September 30, 2025, YiduCore had processed nearly 7 billion authorized medical records, serving over 10,000 hospitals nationwide, with its disease knowledge graph covering virtually all known conditions. This foundation enables reliable deployment of agent ecosystems. At the clinical application level, YIDU TECH has collaborated with experts from top institutions like Peking Union Medical College Hospital and Sun Yat-sen University Cancer Center to develop over 280 specialized agents covering cardiology, oncology, and hematology, among other fields, for tasks such as辅助诊断, risk assessment, smart nursing, and medical record generation. A standout example is the Level 3 traceable medical record generation agent, which uses a hybrid architecture combining knowledge and factual constraints to ensure accuracy and support seamless integration with electronic health records. At Peking University Cancer Hospital, the traceable AI medical record辅助生成系统 was recognized as an exemplary innovation at CHIMA.
The viability of any new technology depends on its real-world applicability. YIDU TECH's recent track record is telling: by April 2026, its AI Middle Platform had been deployed in over 40 top-tier hospitals in China. The Yidu Smart Loop app is now available to doctors, with its clinical version supporting deep integration into hospital information systems to embed intelligent decision-making into daily workflows. This rapid adoption signals that medical large models are moving beyond experimental stages into practical clinical integration.
Notably, on April 20, YIDU TECH issued its first annual profit forecast since its founding 11 years ago, projecting a net profit of 55 to 70 million yuan for the 2026 fiscal year. Citigroup promptly raised its target price for the company to HK$11, highlighting Yidu Smart Loop's potential to deepen engagement with doctors and introduce token-based payment models. From early hospital partnerships to benchmark projects and now profitability, YIDU TECH's commercial pathway is gaining traction.
Looking ahead, AI is poised to become a core component of hospital digital productivity. Supported by macro policies and healthcare funding, alongside growing demand for intelligent hospital transformation and scalable AI benefits, medical AI is opening up substantial market opportunities. Globally, MarketsandMarkets predicts the medical AI agent market will grow at a CAGR of 44.1%, reaching $6.92 billion by 2030. In China, the world's largest single-payer healthcare system, there is significant potential for AI-driven decision support, specialized disease databases, and intelligent operational systems.
Future hospital competitiveness will depend not only on bed capacity but also on digital productivity. YIDU TECH's evolvable agent development and collaboration framework provides hospitals with infrastructural assets that lower adoption barriers while accumulating specialized knowledge, ultimately enhancing treatment quality and operational efficiency in the big data era.
However, challenges remain. YIDU TECH must help hospitals overcome concerns about AI safety and data responsibility while ensuring compatibility with other providers and building robust industry standards. Although AI Middle Platform 3.0 reduces development complexity, transitioning hospitals from passive procurement to active creation requires user education and knowledge system development.
In conclusion, medical AI is shifting from a race for technological presence to a focus on reliability and value. Rather than pursuing futuristic ambitions, YIDU TECH is strengthening data capabilities and knowledge graphs to build value from the ground up. The agent development and collaboration path unveiled at CHIMA 2026 represents a systematic, practical blueprint for AI-enabled hospitals, signaling a profound transformation in how medical AI is produced and consumed. Hospital administrators will increasingly seek standardized platforms to cultivate their own evolving agent systems tailored to clinical needs. As embodied in YIDU TECH's AI Middle Platform 3.0 philosophy, the goal is not just building stronger models but creating an engineered system where agents can be developed, evaluated, and collaboratively enhanced—a clear direction for the ongoing digital revolution in healthcare.
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