A smart fitness tracking system with AI-powered workout insights
This app combines structured workout tracking with intelligent feedback. It analyzes your last session and provides actionable recommendations for progression, recovery, and performance. With a full exercise library, customizable programs, detailed history, and personalized nutrition targets, it is built to support consistent training and long-term results.
A fitness system built for consistency, progression, and clarity
This app was designed around a core problem in fitness: most users track workouts, but very few truly understand how to progress. It solves that by combining structured logging with intelligent analysis, giving users a clear view of what they’ve done and what they should do next.
Users can follow pre-built programs or create fully customized routines, track every exercise with detailed history, and monitor progress across time through visual charts and calendar views. On top of that, the system provides personalized recommendations, nutrition targets, and daily goals — turning raw workout data into actionable insight and long-term results.
Complete Stack
Core stack
Flutter
Dart
Riverpod
Sqflite
SQLite
UI & UX
Material UI
Google Fonts
Flutter Animations
Carousel Slider
Staggered Animations
Data & Storage
Sqflite
Shared Preferences
Path Provider
Offline-first architecture
Integrations & Features
Google Generative AI
HTTP
Charts (Syncfusion)
Calendar Timeline
Permissions Handler
Audio & Vibration
Background Tasks
Capabilities
Fitness Features
AI Workout Review
After each workout, the system analyzes your performance and generates intelligent feedback. It suggests how to adjust volume, intensity, and recovery to help you progress consistently and avoid stagnation.
Workout History & Calendar
Track every session through a structured history system with a calendar view and activity heatmap. Easily review past workouts, monitor consistency, and understand long-term progress.
Exercise Library & Progress Tracking
Access a library of exercises with instructions, muscle group targeting, and visual charts. Track your performance on each exercise over time and clearly see strength and volume improvements.
Programs & Full Customization
Follow structured training programs or build your own from scratch. Add exercises, adjust sets and reps, and create a fully personalized training system tailored to your goals.
Smart Metrics & Daily Goals
Automatically calculated BMI, calorie intake, and hydration goals based on your profile. The system helps you stay aligned with your fitness objectives beyond just workouts.
Built-in Training Tools
Includes practical tools like a plate calculator, timers, and daily tracking utilities. Designed to support real training sessions without needing external apps.
Engineering
Engineering Highlights
Offline-First Architecture
The app is built around a local SQLite database using Sqflite, allowing full functionality without an internet connection. Workouts, history, programs, and user data are stored locally, ensuring fast performance and reliability even in offline scenarios.
AI Integration Layer
AI-powered workout reviews are generated using external APIs, isolated from core functionality. This ensures the app remains fully usable offline while enhancing user experience with intelligent insights when connectivity is available.
Modular State Management
State is managed using Riverpod, enabling a scalable and maintainable architecture. Features such as workouts, programs, metrics, and settings are isolated into independent providers, reducing coupling and improving testability.
Structured Data & Tracking
Workouts, exercises, logs, and programs are modeled through a structured local schema, allowing efficient querying and historical tracking. This enables features like progress charts, calendar views, and per-exercise analytics without performance bottlenecks.
Lessons learned
What this project taught me
Designing Offline-First Systems
Building around a local database changed how features are designed. Instead of relying on APIs, the system had to be fast, reliable, and fully functional offline, which required careful data modeling and synchronization thinking from the start.
Turning Data into Insight
Tracking workouts is simple, but providing meaningful feedback is not. Implementing AI-based reviews highlighted the gap between raw data and actionable insight, and the importance of presenting recommendations that users can actually follow.
Managing Complex State
Workouts, programs, logs, metrics, and settings all interact with each other. Structuring this using Riverpod required clear separation of concerns and disciplined state management to keep the app scalable and maintainable.
Building for Real Users
Fitness apps are used daily, which means small UX decisions matter. The focus shifted toward speed, clarity, and minimal friction so users can log workouts quickly and stay consistent over long periods of time.
Ermin Koric
Software made simple, thoughtful, lasting.
Great software isn’t decoration — it’s architecture, logic, and deliberate structure.
Developed by — Ermin
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