Case study
Coach Calories
Public beta — temporary URL (calories.lovany.fr).
Nutrition-tracking PWA: log a meal in plain language and the AI resolves the foods and macronutrients. Personalized daily targets, barcode scanning, history and trends.

Context
Nutrition-tracking app designed to make daily calorie and macronutrient counting simple, without tedious data entry.
Problem
Classic nutrition apps make you weigh and search for every food in a database. Users give up before the habit sticks.
Solution
A PWA where users describe their meal in plain language. The AI automatically resolves the foods, quantities and macronutrients. Personalized daily targets replace manual counting.
My role
Product design, architecture, full-stack development, AI integration (OpenRouter), PWA, passwordless authentication and deployment.
Architecture
- TanStack Start and React for a fast PWA
- Convex for data, auth and server functions
- OpenRouter for AI meal resolution
- Tailwind v4 for the interface
- Vercel for deployment
Challenges addressed
- Turning free-form descriptions into structured foods with macronutrients
- Offering a smooth passwordless experience (OTP + Google)
- Keeping the app fast despite AI calls
- Respecting privacy: photos are temporary and never stored
Verifiable results
- Installable PWA on iOS and Android
- Automatic meal resolution from plain language
- Personalized daily targets (calories, protein, carbs, fat)
- Barcode scanning, history and trends
- Passwordless authentication (magic link + Google)
Next steps
Add photo-based meal scanning, goal-adapted meal suggestions and a family mode.