Weight management has become a crucial concern due to the rising obesity rates and supplementary health-related issues caused by improper weight regulation. It is determined as a contributing factor to Body Dysmorphic Disorder (BDD), a mental health condition that strongly impacts emotional well-being and often leads to social isolation. To address these challenges efficiently, the integration of technology into weight management has emerged as an essential solution. For consistent monitoring and tracking of user’s calorie intake and expenditure, we have developed a framework that assists healthy and sustainable weight management. This framework initialized by leveraging personal user data to provide personalized daily calorie goals for food intake, including macro–micronutrient recommendations. It emphasizes real-time recalibration and incorporates Application Programming Interface (API) with food nutritional data to track daily weight management metrics consistently. The system utilized food data through an API that is able to provide regional food item calories, including macro–micronutrient breakdowns, such as Gujarati food items, while highlighting the regional local food items. Unlike traditional nutrition and fitness systems (other applications), local food is generally not addressed and does not incorporate Natural Language Processing (NLP) for food search queries. In our system, we leveraged NLP and high-resolution photographic representation of queried food items. This approach ensures optimal search results by enhancing search accuracy with NLP, which supports diverse languages and API integration with high-resolution images for precise identification of food items. The designed system framework can resolve improper weight management and become a key director for human health.