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WEUE came to us with nothing but an idea: a mobile app that could scan a food label, understand what’s actually in it, and tell someone straight away whether it fits their diet, allergies, or health conditions. We took it from a blank page to a fully working app, shaping the product vision, building the AI-powered label recognition engine, designing and developing the app end-to-end, and getting it live on the Google Play Store.
Reading an ingredients label sounds simple until you’re the one standing in a supermarket aisle with a nut allergy, trying to work out if “may contain traces” applies to what’s in your trolley. For someone managing diabetes or a dietary restriction, that moment repeats dozens of times a week, and the cost of getting it wrong isn’t hypothetical. It’s a reaction, a spike, a trip to the chemist, or worse.
WEUE had the idea but nothing built. No prototype, no dataset, no app. Just a clear sense that people needed a faster, smarter way to check whether a food fits their health profile before they eat it, and a want to help people track their overall diet and nutrition at the same time. They needed a partner who could take that idea and turn it into something that actually works on a phone, reads a label accurately, and gives a clear answer people can trust.
A user builds a health profile once, allergies, ailments, and dietary requirements, then simply takes a photo of any ingredients label. The app reads the label, checks every ingredient against that person’s profile, and gives a clear answer on whether to eat it, alongside the meal’s nutritional breakdown.
We delivered exactly what was scoped: a working app, built from an idea with no existing prototype, that reads food labels, checks them against a personal health profile, and helps people track their diet over time. It went live on the Google Play Store, giving WEUE a real product in the hands of real users rather than a concept stuck on the drawing board. The build itself performed exactly as intended end-to-end, from label scan through to health advice and food tracking.
| Industry | Health & Wellness |
| Model / LLM | OpenAI API for ingredient safety checks, OCR for label text extraction |
| Architecture | React Native app (iOS & Android) with a Python Flask backend |
| Data Sources | Structured ingredient datasets mapped to allergies, ailments, and dietary requirements |
| Infrastructure | MongoDB Atlas database, AWS-hosted backend |



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