Fangzhou’s ‘XingJie’ LLM Secures Key National Filing, Paving Way for Advanced AI Chronic Care Innovations

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SHENZHEN, China, Nov. 02, 2025 – Fangzhou Inc. (“Fangzhou” or the “Company”) (HKEX: 06086), a prominent provider of AI-powered internet healthcare solutions, received a Generative AI Service Filing Certificate during the inaugural Guangdong Provincial LLM Filing Conference held in Shenzhen.

During the conference, Dr. Xie Fangmin, Founder, Chairman, and CEO of Fangzhou, stated: “The successful introduction of the ‘XingJie’ Large Language Model (‘XJ LLM’) signifies a new achievement in Fangzhou’s progress in AI-powered chronic disease management. Leveraging this accomplishment, we plan to further refine our models and expand our AI+H2H (Hospital-to-Home) healthcare ecosystem, blending advanced AI functionalities with expert medical services to ensure every user benefits from intelligent, convenient, and customized care.”

a man giving speech at a conference with a blue background
Dr. Xie Fangmin delivered a speech at the first Guangdong Provincial LLM Filing Conference

Fangzhou’s proprietary XJ LLM, an AI model specifically designed for healthcare, has officially completed the National Generative AI Service Filing (Filing No. Guangdong-XingJie-202509120089) with the Cyberspace Administration of China. The Company’s introduction of two leading models—XJ LLM and XS LLM (unveiled in September 2025)—reinforces its leadership in AI-driven chronic disease management. This accomplishment highlights the imminent shift in chronic disease management from conventional, reactive inquiry-based care to an AI-driven model offering predictive insights and tailored treatments.

As a foundational component of Fangzhou’s AI+H2H ecosystem, the XJ LLM is founded on three core innovations—technological progress, application evolution, and operational streamlining—which together redefine the service experience. XJ LLM integrates emotional perception with intent reasoning to anticipate user requirements, functioning as a central orchestrator for various models to achieve peak speed and performance. This transition from app-centric features to AI-powered experiences facilitates intuitive interactions and autonomous task completion. The XJ LLM’s knowledge base continuously adapts to real-world information, thereby lowering maintenance expenses and enabling broad AI functionalities across comprehensive enterprise workflows.

The successful registration of the XJ LLM marks a significant achievement within Fangzhou’s AI-enhanced chronic disease management ecosystem. Together with the earlier introduced XS LLM, this two-model framework establishes an integrated AI+H2H ecosystem offering extensive management solutions across specialized disease domains. This ecosystem currently provides comprehensive intelligent services for areas such as AI+weight management and AI+psoriasis care, furnishing personalized medication advice and complete support encompassing disease education, specific interventions, and continuous tracking.

Fangzhou has established strategic collaborations with several prominent pharmaceutical firms, such as Novo Nordisk, Innovent Biologics, and Fosun Pharma, with the goal of co-developing cutting-edge frameworks for AI-assisted disease management, thereby expediting the industry’s shift towards intelligent, data-driven healthcare.

Moving ahead, Fangzhou intends to broaden its AI-powered solutions throughout the entire scope of chronic disease management by utilizing its XS LLM and XJ LLM models. The company steadfastly upholds its commitment to its goal of fostering “better health for all” through the deployment of advanced technology, supporting the vision of a healthier China.

About Fangzhou Inc.
Fangzhou Inc. (HKEX: 06086) stands as China’s premier online platform for chronic disease management, catering to 52.8 million registered users and 229,000 physicians (data as of June 30, 2025). The Company specializes in providing customized medical services and AI-supported precision medicine solutions. For further details, please visit .

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Disclaimer: This press release includes forward-looking statements. Actual outcomes could vary significantly from those projected due to multiple factors. Readers are advised against placing excessive reliance on these statements.