Case study · Client project · sole developer

SimplifyRad

Turn a photographed or uploaded medical report into an explanation a patient can actually read.

platforms from one Flutter codebase: 3
developer, from app to API: 1

Context

SimplifyRad delivers plain-language insights on medical reports. A user photographs or uploads a report as an image or PDF and gets back an explanation they can read without a clinical background.

I built and delivered the full product on my own: a Flutter app for Android, iOS and web, and the Django and PostgreSQL API behind it.

What I built

Flutter app: One app for Android, iOS and web: capture or upload a report, read the explanation as rendered Markdown, and browse the history of past reports.
Report pipeline: The Django API accepts an image or PDF, runs OCR to extract the text, and sends that text to a generative AI model that returns a plain-language explanation. Uploads retry on failure.
Accounts & access: E-mail OTP verification, password reset and guest access.

Architecture

Clients
- Flutter app
  - Android · iOS · web
  - capture / upload · history
Application
- Django API
  - e-mail OTP · password reset · guest access
  - report upload (image / PDF)
  - OCR text extraction
  - prompt → plain-language explanation
  - report history
Data & services
- PostgreSQL
- OCR
- Generative AI model

A single Flutter codebase for Android, iOS and web talks to a Django API backed by PostgreSQL. The API runs OCR on each uploaded report and sends the extracted text to a generative AI model.

Key decisions

One Flutter codebase for three platforms
Android, iOS and web all ship from the same Flutter app, built and delivered by one developer.
OCR first, then the model
The API extracts the report text with OCR and sends that text, rather than the original image or PDF, to the generative AI model.

Results

Full product built entirely by me: a Flutter app for Android, iOS and web, and a Django/PostgreSQL API.
Delivered privately to the client.