Core Viewpoint - Zhongkang Holdings (02361) is upgrading its strategy from a "provider of intelligent solutions in the life sciences" to an "AI technology service company based on health industry data elements and ecological resources" [1] Group 1: Strategic Upgrade - The company is transitioning from "data technology services" to "AI decision-making and intelligent services," leveraging a comprehensive capability of "data + model + scenario + ecology" [1] - The dual-domain large model includes: (1) Zhuomuniao (medical large model), which is trained on medical literature, case histories, and pharmaceutical knowledge graphs, evaluated by medical experts for enhanced professionalism and accuracy; (2) Tiangong No. 1 (decision-making large model), which integrates diverse market data and industry logic with medical knowledge to create actionable marketing strategies and resource allocation plans [1] Group 2: Data Resources and Industry Insights - The company possesses a diverse range of health industry data resources covering medical institutions, health check-up centers, and pharmacies, establishing a comprehensive data system from hospitals to outpatient services, online to offline, and prevention to treatment [1] - With 18 years of industry know-how, the company decodes the business logic behind the data, dismantling complex business scenarios to assist in key decision-making [1] Group 3: AI Service System and Team Collaboration - The company has built a complete AI service system from foundational to front-end applications, capable of meeting diverse needs from SMEs to large corporate clients [2] - The team and partners combine top-tier AI technology with extensive pharmaceutical experience, ensuring the integration of technology with medical scenarios to create quantifiable value [2] - Under the new strategic guidance, Zhongkang will leverage its core capabilities to drive AI implementation across four key scenarios: health industry marketing, medical services, pharmacies, and health management [2] Group 4: Future Development - The company will adhere to its established development strategy, building an efficient collaborative ecosystem of health industry intelligent entities based on industrial-level data, continuously leading the industry into a new era of intelligence [3]

Core Viewpoint - Zhongkang Holdings (02361.HK) is transitioning from a "provider of intelligent solutions in the life sciences" to an "AI technology service company based on health industry data elements and ecological resources" [1] Group 1: AI Models - The company has developed a dual-domain large model: - Zhuomuniao (medical large model) is trained on medical literature, medical records, and pharmaceutical knowledge graphs, demonstrating enhanced professionalism and accuracy in understanding complex medical terminology and compliance requirements [2] - Tiangong No. 1 (decision-making large model) integrates diverse market data and industry logic accumulated over years, along with medical knowledge, to convert medical cognition into actionable marketing strategies and resource allocation plans, aiming to close the value loop from "medical cognition" to "business results" [2] Group 2: Data Resources and Industry Insights - The company possesses a diversified health industry data resource that covers a wide range of medical institutions, health check-up centers, and pharmacies, creating a comprehensive data system that spans from hospitals to outpatient services, online to offline, and prevention to treatment [3] - With 18 years of industry know-how, the company decodes the commercial logic behind the data and dissects complex business scenarios to assist in key decision-making [3] Group 3: AI Service System and Team Collaboration - The company has established a complete AI service system that ranges from foundational infrastructure to front-end applications, capable of meeting diverse needs from small and medium enterprises to large corporate clients [4] - The team and partners combine top-tier AI technology with extensive pharmaceutical experience, ensuring the integration of technology with medical scenarios to deliver quantifiable value [4]