EFN: Science-Based Fitness & Nutrition App on iOS and Android
Overview
A French fitness coach needed a fully personalised nutrition and training app for her audience — one that went beyond generic calorie counters. The app had to generate scientifically accurate macro targets, 7-day meal plans, and training programs based on each user's body composition, using methods like Mifflin-St Jeor BMR, CUN-BAE body fat estimation, and FFMI-based tier classification..
The Challenge
A French fitness coach needed a fully personalised nutrition and training app for her audience — one that went beyond generic calorie counters. The app had to generate scientifically accurate macro targets, 7-day meal plans, and training programs based on each user's body composition, using methods like Mifflin-St Jeor BMR, CUN-BAE body fat estimation, and FFMI-based tier classification.
Our Solution
We built a cross-platform Flutter app (iOS + Android) with a precision nutrition engine covering 5-tier body composition classification, 12-week projection modelling, real-time macro logging with barcode scanning, and progressive overload training tracking. The Node.js backend powers 30+ API endpoints, RevenueCat subscription management with a behaviour-triggered 72-hour trial, GitHub Actions CI/CD to AWS EC2, and full EN/FR bilingual support.
Results
Live on App Store and Google Play
48 automated tests covering the full calculation engine
72-hour behaviour-triggered trial with graceful read-only degradation
Full EN/FR localisation across 30+ services
“The precision of the nutrition engine is unlike anything else on the market. It handles complexity that most apps just ignore.”
Tech Stack
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