Project Summary
Supermaty is an innovative platform in the Netherlands that completely changes how people buy groceries. Instead of the traditional method of searching for items one by one (like "milk," "eggs," "bread"), Supermaty introduces a highly personalised "Shopping Bag" concept.
Think of the experience of going to a gym where a mentor gives you a specific diet plan to follow. Supermaty recreates this convenience digitally. The user does not need to hunt for an external coach or a pre-made list; the app creates one for them.
From the moment a user registers, the app asks a series of questions about their habits, goals, and preferences. Based on these answers, the system instantly generates a customised "Shopping Bag." It transforms grocery shopping from a boring chore into a personalised lifestyle experience tailored to the user from day one.
About the Client
The client is a forward-thinking startup based in the Netherlands. They identified a growing gap in the European market: consumers care deeply about what they eat (allergies, calories, ethics), but supermarkets make it hard to shop by these categories.
The client wanted to build a bridge between dietary goals and supermarket shelves. Their vision was a platform where a user could look at a meal plan or a fitness goal and instantly have the right groceries ready to buy, without doing the math or searching for ingredients manually.
The Challenge
Building Supermaty wasn't just about building a website; it was about gathering massive amounts of hidden data. We faced several major hurdles:
The "Walled Garden" of Data: Supermarkets in the Netherlands do not share their data. They don't have public systems (APIs) that let other apps talk to them. This meant we had to find a way to match the product name and specification with its ingredients and metadatas which was not available from the supermarket.
Matching "House Brands": Every supermarket has its own private label (e.g., "Store Brand Oats"). A computer usually treats "Store Brand Oats" from Shop A as a totally different item than "Store Brand Oats" from Shop B. We needed the system to understand that they are essentially the same thing, so users could compare prices.
The "Pinch vs. Jar" Math: A recipe might ask for "50 grams of peanut butter," but the store sells a "350-gram jar." The system needed to be smart enough to convert recipe amounts into actual products to buy.
The Solution
The Supermaty project successfully moved from a complex idea to a working Minimum Viable Product (MVP).
Proof of Concept: We proved that a personalised, lifestyle-based shopping experience is possible and functional.
Technical Victory: We successfully acquired data from the hardest sources, a feat many other developers had failed to achieve.
Savings for Users: Users can now instantly see which supermarket is cheaper for their specific diet plan, saving them money on every shop.
Massive Data Handling: The system currently manages 200,000 highly detailed products with real-time updates, proving the architecture is stable and scalable.
Legal & Safe: We ensured that all data-gathering methods were legally compliant and sustainable for the long term.
The Outcome
The Supermaty project successfully moved from a complex idea to a working Minimum Viable Product (MVP).
Proof of Concept: We proved that a personalised, lifestyle-based shopping experience is possible and functional.
Technical Victory: We successfully acquired data from the hardest sources, a feat many other developers had failed to achieve.
Savings for Users: Users can now instantly see which supermarket is cheaper for their specific diet plan, saving them money on every shop.
Massive Data Handling: The system currently manages 200,000 highly detailed products with real-time updates, proving the architecture is stable and scalable.
Legal & Safe: We ensured that all data-gathering methods were legally compliant and sustainable for the long term.