Case study
Bringing Bloomplate to iOS and Android
Bloomplate delivers personalized meal plans developed with doctors and nutrition specialists. We turned the web platform into a native mobile app with AI meal scanning, habit tracking, and subscriptions straight from the App Store and Google Play.
The client
Personalized nutrition, backed by specialists
Bloomplate is a Romanian nutrition platform that gives users a new meal plan every week, tailored to their eating style, calorie needs, and chosen goal: from weight maintenance and anti-inflammatory eating to PCOS, endometriosis, thyroid health, or fertility.
The plans are developed with doctors and nutrition specialists. When we started working together, the web platform was already serving paying subscribers, and a mobile app was the natural next step.
The challenge
From the browser to the kitchen
A meal plan gets used in the kitchen and at the supermarket, not at a desk. The app had to bring the experience to the phone and add what a browser cannot do well.
- 01A native app for iOS and Android, built on the existing backend without disrupting the web platform subscribers rely on every day.
- 02Fast logging for unplanned meals: users wanted the nutrition facts of a plate without searching for and weighing every ingredient.
- 03Subscriptions sold through the App Store and Google Play, kept in sync with the ones already paid through Stripe on the web.
- 04Compliance with Apple and Google rules for health apps: scientific sources for recommendations, in-app account deletion, and correctly localized prices.
Our approach
How we built it
01
One codebase, two platforms
We built the app in React Native with Expo and TypeScript. The same code runs on iOS and Android, and store builds go through an automated pipeline.
02
A dedicated mobile API
We added a separate mobile module to the Django backend. The web platform stayed untouched, and the new logic (calorie targets, daily tracker, notifications, subscriptions) is covered by automated tests.
03
AI Food Scan
An OpenAI vision model identifies the dish, its ingredients, and their weights from a single photo. Nutrition values come from our own food database, which grows with every scan, so results stay consistent and AI costs drop over time.
04
Production-ready from day one
Push notifications scheduled in each user’s time zone, content automatically translated into English, error monitoring with Sentry, and product analytics with PostHog.
Features
What the app does
01 / 06
Weekly meal plan
A new plan every week with breakfast, lunch, dinner, and snacks. Any meal you don’t like can be swapped for another one that fits your goal.
02 / 06
AI Food Scan
Take a photo of your plate and within seconds see the ingredients, weights, calories, and macros. If the AI gets an ingredient wrong, you correct it and the values update instantly.
03 / 06
Step-by-step recipes
A cooking mode with checkable steps, adjustable servings, and nutrition facts per serving.
04 / 06
Automatic shopping list
The list is generated from the meal plan, grouped by product category, and can be exported as a PDF.
05 / 06
Habits and progress
A habit tracker for hydration, sleep, movement, and eating, with streaks and monthly calorie and macro statistics.
06 / 06
Partner benefits
Exclusive discounts at partner restaurants, products, and brands, right inside the app.
The result
At a glance
iOS + Android
from a single codebase
11
health goals supported in the app
2 languages
Romanian and English, with recipes translated automatically
Technologies
The tech stack
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