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// Case studies · Healthcare / mobile app

Hand in Hand

Treatment companion for GLP-1 medications

App for patients under GLP-1 treatment: dose reminders, daily symptom check-ins, an AI assistant grounded in official leaflets and automatic clinical alerts, with LGPD consents.

Client
Hand in Hand
Period
2026
Status
MVP delivered
Stack
FlutterFirebase + Cloud FunctionsGeminiRiverpod
Hand in Hand: Treatment companion for GLP-1 medications

// The challenge

Patients on injectable GLP-1 treatment miss doses, don't record side effects and have nobody to ask between appointments. The client needed a working MVP in 30 days to validate the product with doctors and a distributor.

// What we delivered

Flutter app for iOS and Android with clinical onboarding and LGPD consents, dose reminders, daily check-in (dose, symptoms, mood, weight), an AI assistant that answers based on official leaflets and guidelines and escalates to the medical contact in severe cases, and an automatic clinical alert engine. Firebase backend with serverless functions and a marketing website.

30 days
from briefing to delivered MVP
14
commercial brands covered by the reference base (8 active ingredients)
iOS + Android
from a single codebase, plus the website

Description

Hand in Hand accompanies patients during treatment with GLP-1 medications (such as semaglutide and tirzepatide). It reminds them of the dose, records how they feel, answers questions based on official leaflets and flags when a sign deserves medical attention. Clinical responsibility stays with the doctor; the app organizes the routine and gives visibility.

Key Features

  • Clinical onboarding: treatment data, medication, consents and terms under LGPD (Brazil’s data protection law).
  • Dose reminders: local notifications on the day and time of the injection.
  • Daily check-in: dose taken, symptoms on a scale, side effects, mood, weight and notes.
  • AI assistant: answers grounded in official leaflets and clinical guidelines, escalating to the medical contact in severe cases.
  • Clinical alerts: rules engine that detects risk patterns and avoids repeated alerts.
  • History: adherence, symptoms, weight and conversations throughout the treatment.
  • Account and data deletion: full flow required by the stores and by LGPD.

Technologies Used

  • Mobile: Flutter with Riverpod and go_router, one codebase for iOS and Android
  • Backend: Firebase (Auth, Firestore with ownership rules, Cloud Functions in TypeScript) and Gemini via a serverless function, secrets in Secret Manager
  • Website: static pages on Vercel (presentation, privacy and support)

Screens

Patient dashboard
Patient dashboard
Daily dose and symptom check-in
Daily dose and symptom check-in
AI assistant grounded in the leaflets
AI assistant grounded in the leaflets
Progress and history
Progress and history
Profile and treatment
Profile and treatment

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