Our own product2025

FitZen

AI-powered diet and nutrition tracking.

iOSAndroidWeb

Let’s build something like this

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AppAMG / 25

Project: Our own product
Our role: Product · Mobile development · Backend · Release
Duration: 5 months

01 / PRODUCT & APPROACH

From a meal to an everyday habit.

FitZen is our own product for making nutrition tracking part of everyday life. Photo-based meal analysis, daily tracking and recipe creation come together in a connected experience on iOS and Android.

Nutrition tracking turns into a chore and gets abandoned when meal logging and planning are scattered across screens. AI can ease that, but with two traps: presenting model output as a health claim, and depending on the model itself. When a provider retires a model version, every released build of the app breaks at once.

The daily experience

01
Capture a meal
Start with a food photo from the camera or gallery.
02
Review the result
Review estimated foods, portions and nutrients, then add them to the daily log.
03
Follow your day
Track meals, macros, water and activity alongside your goals.

DECISIONS THAT SHAPED THE PRODUCT

/ 01

Turning AI into a usable workflow.

Photo selection, preview, analysis and results are separate states. Users can see when analysis is running and when a result is added to their diary. Nutrient estimates support everyday logging without presenting model output as a medical conclusion.

/ 02

A product beyond a single screen.

Daily history, water and activity tracking, recipe creation and subscription access have distinct responsibilities. Firebase records and local caching support access to historical data. A separate web dashboard handles content and management alongside the mobile product.

THE RESULTING PRODUCT

From a feature to an everyday experience.

Live on iOS and Android in 11 languages, rated 4.4 on the App Store. Daily history, water and activity tracking, recipe generation and the subscription flow sit in one product, with content and management in a separate web panel. A performance pass prioritised startup tasks, removed unused libraries and split a 1,300-line subscription service into modules.

02 / Inside the product

The experience, on screen.

Open a screen to explore the details.06 images

03 / Scope & details

The details make the experience.

01
Food recognition from a photo
02
Barcode scanning against an international product database
03
Firebase records, daily history and local caching
04
Macro and micro tracking, water and workout integration

AI meal planningPhoto recognitionMacro trackingRecipe creatorWater trackingProgress analytics

Technology

React NativeTypeScriptNode.jsFirebaseOpenAI

INSIDE THE PRODUCT

The engineering behind the interface.

Systems we built and concrete problems we addressed in this project.

A controlled path from photo to analysis

Camera and gallery feed the same analysis flow. Permission denial, cancelled selection and invalid image data are handled as separate states, making each step understandable.

A retired model does not break the app

The model name is embedded in the mobile bundle; when the provider retires a version every released build gets a 404. An alias table in the Cloudflare Worker proxy maps retired names to a living model; exactly that happened for gpt-5.2-chat-latest on 3 September 2026 and no store update was needed.

Notifications and subscriptions on the server

Morning and evening notifications go out per language from Pub/Sub schedulers, and a smart scheduler running every ten minutes respects the user’s time zone. A RevenueCat webhook writes entitlements, a separate job reconciles expired premium, and dietitian session credits are consumed through onCall functions.

Explore the product screens ↓App Store ↗Google Play ↗Visit site ↗