Building a Local-First Flutter App with Drift, SQLCipher, and Riverpod 3.0

rahul kumar — Mon, 06 Jul 2026 17:56:42 +0000

Building local-first apps is becoming the standard for modern mobile developers. Users expect high performance, offline functionality, and strict privacy controls over their personal data.

In this article, we will look at the core architecture patterns for building a secure, offline-first application in Flutter using Drift (SQLite), SQLCipher (local database encryption), and the new Riverpod 3.0 code generator.

The Security Challenge

For health, fitness, or financial logs, storing raw text on a device is a vulnerability. If a device is compromised, database files can be easily extracted.

To solve this, we initialize Drift on top of an encrypted database connection using SQLCipher. Here is the conceptual flow:

Retrieve a secure key (e.g., from Flutter Secure Storage).
Open the SQLite database connection using EncryptedDatabase.
Generate Drift tables automatically using @DriftDatabase.

State Management with Riverpod 3.0

We decouple UI from logic using Riverpod's new generator syntax. For example, to track the active workout state:

@riverpod
class ActiveWorkout extends _$ActiveWorkout {
  @override
  WorkoutState build() => const WorkoutState.idle();

  void startWorkout(WorkoutPlan plan) {
    state = WorkoutState.running(plan);
  }
}

Get the Complete Source Boilerplate

If you want to skip the configuration hassle and start coding features immediately, I have packaged my complete production-grade codebase—including full Gemini AI integration, localizations (English, Hindi, Marathi), a 3D body mapper UI layout, and a pre-seeded database of 1,000+ exercises:

👉 COMPLETE STARTER KIT: https://rahulsaroh.gumroad.com/l/sovgjy
Use launch coupon code LAUNCH30 for 30% off!

You can download and check app on play store too..
https://play.google.com/store/apps/details?id=com.aigymmentor.app

How I Built an Offline-First AI Gym App in Flutter with SQLCipher + Gemini AI

rahul kumar — Mon, 08 Jun 2026 14:10:17 +0000

The Problem I Was Solving

Most fitness apps sync your health data to the cloud. I wanted an app where everything stays on-device — encrypted and private. No subscriptions, no cloud dependency.

So I built AI Gym Mentor in Flutter.

The Architecture

1. Encrypted Local Database with Drift + SQLCipher

The biggest technical challenge was implementing encrypted local storage. I used Drift (formerly Moor) as the ORM and SQLCipher for encryption on top of SQLite.

This means all workout logs, body measurements, and user data are AES-256 encrypted on-device.

2. Google Gemini AI Integration

I integrated the Gemini AI API to provide real-time coaching. After a workout, the app sends your session data to Gemini and returns personalized feedback, recovery suggestions, and progression advice.

The key was keeping the prompt context tight — sending only relevant recent session data rather than the full history.

3. Riverpod 3.0 State Management

The app uses Riverpod 3.0 with annotated generators for clean, scalable state management. This was essential given the complexity of syncing Wear OS data, chart state, and AI responses.

4. Full Tech Stack

Flutter 3.22+ (iOS, Android, Web)
Riverpod 3.0 (Annotated Generators)
Drift + SQLCipher (encrypted local DB)
Google Gemini AI
GoRouter 17.2+
Wear OS sync
fl_chart for analytics (1RM, volume, body measurements)
Lottie + Shimmer animations
1,000+ exercise database
Multi-language: English, Hindi, Marathi

Why I Packaged It as a Template

After finishing the app, I realized it had taken months to build all these pieces together correctly. The SQLCipher setup alone took days. The Gemini integration required multiple iterations.

So I packaged the complete source code as a developer template — AI Gym Mentor — so other developers can build on top of it instead of starting from scratch.

What's Included

Complete, buildable Flutter source code
README with full setup guide
Seeded exercise database (exercises.json)
.env.example for Gemini API key setup

The template is available here: https://rahulsaroh.gumroad.com/l/sovgjy

Launch price: $29. Use code LAUNCH30 for 30% off (first 10 buyers).

Happy to Discuss

If you have questions about the SQLCipher + Drift setup, the Gemini integration pattern, or the Riverpod architecture — drop a comment below!

DEV Community: rahul kumar