NutriGenie

AI Nutritionist

Inspiration

Nutrition remains a critical yet underserved area in preventative health. Many apps today stop at calorie counting or generic advice, leaving users without actionable, personalized guidance. We envisioned NutriMeal as a step into the next frontier of health—an AI-powered nutrition assistant that proactively supports physical wellness by transforming data into real, everyday health decisions.

What it does

NutriMeal leverages machine learning to analyze a user’s dietary needs, lifestyle, and goals, then generates personalized meal recommendations. Beyond tracking, it clusters eating patterns and suggests healthier swaps in real time. NutriMeal also bridges the gap between recommendations and action by automatically generating grocery lists, making it easy for users to follow through on healthier choices.

How we built it

AI & ML: Built clustering models to recognize meal patterns and generate adaptive nutrition recommendations. Data: Leveraged MealDB API for verified nutrient information and synthetic user profiles for development. Backend: FastAPI to power meal analysis, recommendations, and API integration. Frontend: Interactive, user-friendly experience using JS and HTML/CSS. Deployment: Containerized with Docker for scalability and easy deployment.

Challenges we ran into

Normalizing nutrition data from different sources into consistent, machine-readable formats. Designing recommendation logic that is both medically sound and user-friendly. Integrating external APIs under time and rate constraints. Balancing personalization with general wellness guidance without overcomplicating the UX.

Accomplishments that we're proud of

Delivering an end-to-end solution that goes from meal logging → AI recommendations Designing a clean UI that makes complex recommendations feel intuitive and actionable. Demonstrating how AI can bridge the gap between data-driven insights and real-world healthcare impact.

What we learned

How to harness AI not just for analysis, but for behavioral change support in wellness. The importance of combining clean UI/UX with backend intelligence for adoption. Deepened knowledge of APIs, machine learning algorithms, and data processing. Effective team collaboration to move quickly from concept to prototype.

What's next for NutriMeal

Instacart/Amazon Fresh integration: Sync with online shopping tools to automatically import grocery lists into the shopping cart, finding the best prices. Community support: Recipe sharing, progress tracking, and peer encouragement. Scalability: Expand into partnerships with healthcare providers, insurers, and meal kit services.