Design and Real-World Validation of a Multimodal AI-enabled Intelligent Hyperautomation Framework for Weight and Metabolic Health Management: the CNFCD Model

AI-enabled weight and metabolic health management at population scale requires enterprise information systems that transform multimodal data into real-time decision-support workflows. This study proposes the Comprehensive Nutrition and Flexible Caloric Diet (CNFCD) model as a multimodal AI-enabled intelligent hyperautomation framework integrating five human-centered components. Based on real-world operational data from over 110,000 users, an analytical cohort of 18,539 participants generated more than 140,000 longitudinal observations. Results showed significant improvements in body weight, body composition, self-efficacy, and dietary behavior. Key predictors of weight reduction included real-time feedback, slow and mindful eating, and daily green vegetable intake.