Inspiration
We wanted to solve a simple real-life problem: people often waste time searching for recipes and comparing supermarket prices, then end up ordering unhealthy fast food. SmartBite SK helps make cooking easier, cheaper, and faster.
What it does
SmartBite SK suggests what to cook, shows the needed ingredients, compares nearby supermarkets, and recommends the best store based on price, distance, and quality.
How we built it
We built the prototype in Python with Streamlit. We used a simple recipe-matching system, mock supermarket data, and a scoring algorithm to compare stores and estimate the best shopping option.
Challenges we ran into
The biggest challenge was data. Slovak supermarkets usually do not offer easy public APIs for real-time prices and discounts, so we had to design the app around mock data and future integrations.
Accomplishments that we're proud of
We created a working prototype with a clear real-world use case. We are proud that the idea is practical, easy to understand, and designed around actual market limitations.
What we learned
We learned that building useful products is not just about coding, but also about working with incomplete data, designing fallback logic, and keeping the solution realistic.
What's next for SmartBite SK
Next, we want to connect real weekly offers, improve price accuracy, support more stores, and make recommendations more personalized.
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