Consumer AI Application

Recipe Lens: Visual Recipe and Nutrition Tracking

How QPOI built a React Native mobile app that turns food photos into structured recipe suggestions and nutrition estimates through an AI-assisted image workflow.

Duration

3 Months

Platforms

Mobile (iOS & Android)

Tech Stack

React Native (Expo), Gemini Flash

Engagement

MVP Engineering

The Challenge

Tracking nutrition and organising recipes usually involves a lot of manual entry. The client wanted a mobile product that could take food images, generate useful structured outputs, and reduce the friction between taking a photo and recording meal data.

The client needed a solution to:

  • Identify likely dishes: Interpret food images into usable meal information.
  • Estimate nutrition: Generate calorie and macro estimates from photos.
  • Reduce manual effort: Bridge raw images and structured app data.

QPOI's role

  • AI image analysis workflow
  • Local-first mobile architecture
  • Image optimization and upload handling
  • Subscription and monetization setup
Core Features & Engineering

Core features

QPOI delivered a mobile product that combined AI image analysis, local-first data handling, image optimisation, and subscription-ready mobile UX.

Recipe-style food analysis

We built an image-based workflow that turned food photos into structured outputs such as likely ingredients, meal descriptions, and recipe-style data for use inside the app.

Nutrition estimation from images

The app generated calorie and macronutrient estimates from food images, giving users a lower-friction alternative to manual entry.

Local-first storage and meal history

We implemented local storage flows so captured images and meal data could move from temporary capture into persistent app history without relying entirely on live connectivity.

Optimized image handling

We improved analysis responsiveness by resizing and compressing images on-device before transmission, reducing payload size and lowering latency.

Outcome

Delivered an MVP for iOS and Android

Turned image-based nutrition tracking into a usable mobile workflow

Added subscriptions and usage management for launch readiness

Combined AI analysis, mobile UX, and local-first data handling in one product

Mobile Engineering Fundamentals

1

Local data handling

Reliable flows for storing and managing local recipe history and nutrition logs.

2

Subscription logic

Custom hooks to manage complex subscription states and usage caps.

3

Permissions and store compliance

Managed permissions for Camera/Photo Library and implemented compliant IAP restore flows.

Technology Stack

React Native (Expo)TypeScriptGemini 1.5 Flash (Vision)RevenueCatExpo FileSystemAsyncStorage

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