The story of Nomster

Inspiration

Nomster was inspired by a very real student problem: being busy, on a budget, and not knowing what to cook with whatever is left in the fridge. We wanted to build something practical for student life, not just a recipe app, but a meal-planning assistant that helps users turn limited ingredients, budget, and cooking tools into a realistic weekly plan.

What it does

Nomster helps students generate a weekly meal plan based on their ingredients, budget, kitchenware, and preferred mode or goal. It suggests meals, provides recipes for each meal, and creates a shopping list for missing ingredients. The goal is to make meal planning cheaper, easier, and less stressful.

How we built it

We built Nomster with a modern full-stack setup. The frontend was developed to give users a simple and friendly planning experience, while the backend handled API logic, meal-plan generation, recipe storage, and shopping-list creation. We used FastAPI for the backend, PostgreSQL/Supabase for the database, and connected the app through deployed frontend and backend services.

Challenges we ran into

One of our biggest challenges was turning the idea into a working end-to-end product within hackathon time. We had to design the database, connect frontend and backend, manage deployment, and debug issues in API flows, migrations, and data handling. Keeping the generated plans structured and consistent was also a challenge.

Accomplishments that we're proud of

We are proud that we turned a relatable student-life problem into a working product with a clear user flow. We successfully built the core system for meal-plan generation, recipe handling, and shopping-list support. We are also proud that Nomster is not just technically functional, but also practical and easy to imagine using in real life.

What we learned

We learned a lot about building and connecting a full-stack application under time pressure, especially around backend architecture, database design, API integration, deployment, and debugging. We also learned that good product ideas come from simple everyday problems, and that usability matters just as much as technical features.

What's next for Nomster

Next, we want to improve the intelligence and personalization of Nomster. That includes better AI-generated meal suggestions, image-based ingredient input, nutrition-aware planning, stronger user preferences, and smarter budget optimization. We also want to polish the UI and make the experience feel even more interactive and student-friendly.