Inspiration
Most apps available are to-do list making app which are boring and fail to motivate users. We wanted to create an intelligent, engaging platform combining AI scheduling with templates to make daily habits exciting and achievable for everyone.
What it does
AutoRoutine lets users create, schedule, and track daily routines effortlessly. Features include AI-powered routine generation, pre-built celebrity wellness templates, custom task management, completion tracking, and weekly progress analytics to keep users motivated consistently.
How we built it
We developed AutoRoutine using Flutter for the frontend with BLoC state management and Supabase as our backend database. We integrated Google Generative AI for intelligent scheduling and implemented clean architecture with repositories, cubits, and models for maintainability.
Challenges we ran into
We faced UUID validation errors with celebrity templates, struggled with merging template routines with user routines, fixed enum mismatches in the AI generator, resolved snackbar overlap issues with the FAB, and managed complex state across multiple navigation tabs.
Accomplishments that we're proud of
We built an engaging conversational AI flow for routine creation, implemented celebrity routine templates instantly available to all users, created a smart activation system for templates, unified multiple data sources on the home screen, and designed beautiful responsive UI components.
What we learned
State management complexity requires careful architectural decisions. UI polish significantly impacts user experience. Combining local and remote data needs synchronization. Conversational design increases engagement. Clean architecture greatly simplifies debugging and feature extensions. Real-time visual feedback motivates consistency.
What's next for AutoRoutine
We plan to add detailed activity reports, push notifications for reminders, social features for sharing routines, more celebrity templates, gamification with badges, dark mode support, offline functionality, advanced analytics with predictions, and privacy-focused local AI processing.
Built With
- flutter
- geminiapi
- serverpod
- supabase


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