The tongue serves as a map of the body, reflecting overall health, energy balance, and digestion; imbalances in color, texture, shape, moisture or coating signal potential issues. Integrating AI and machine learning into tongue-based diagnosis enhances health assessments’ efficiency, scalability, and objectivity in digital health and integrative medicine. There is some work done applying Machine learning and deep learning models to tongue diagnosis; however, it is often without personalized health assessments. These AI models omit holistic user information, such as lifestyle, and lack systematic decision-making frameworks to analyze the data and provide user-specific health advice. This research bridges the gap in personalized health assessment by proposing a hybrid AI-expert system, which combines an analysis of tongue image with a rule-based questionnaire to enhance diagnostic accuracy. The system has two inference engines based on Large Language Model (LLM) to organize expert knowledge into formulating structured questionnaires. It also uses holistic therapeutic plans based on Ayurvedic principles, offering an intelligent and patient-centered platform. The system will be further enhanced by techniques of Yoga Asanas and Basic Acupressure Points to provide comprehensive healing practices, improving its ability to maintain users’ body balance and overall wellness.