FocusFlow

Inspiration

In a world full of constant pings, endless feeds, and digital noise, it’s harder than ever to stay focused. We were inspired by recent AI research on cognitive load detection and wanted to explore how it could be applied to everyday productivity. The idea was simple: instead of guessing when we’re distracted, what if an app could sense it and gently guide us back into focus?

What it does

FocusFlow helps users understand and improve their attention span. It:

Detects when you’re focused, distracted, or stressed using on-device signals.

Offers real-time nudges and personalized coaching powered by AI.

Tracks focus sessions, provides daily insights, and celebrates progress with streaks and achievements.

Integrates gamification and smart notifications to make productivity rewarding.

Uses RevenueCat to handle subscriptions and in-app purchases seamlessly.

How we built it

Frontend: Built in React Native for cross-platform support.

Backend & Auth: Firebase / Supabase for secure login and data sync.

AI/ML: TensorFlow Lite model for lightweight, privacy-friendly cognitive state detection.

AI Coaching: LLM integration to generate personalized productivity recommendations.

Notifications: OneSignal SDK for smart reminders.

Monetization: RevenueCat SDK for subscriptions, paywalls, and IAP.

Challenges we ran into

Training and optimizing an ML model that runs efficiently on-device.

Balancing helpful AI coaching with a non-intrusive user experience.

Integrating multiple SDKs (RevenueCat, OneSignal, Firebase) in a short timeframe.

Designing a UI that is both calming and engaging.

Accomplishments that we're proud of

Built a working prototype that integrates AI, monetization, and notifications.

Translated an academic research concept into a real, usable app.

Designed a clean and intuitive UI that encourages deep focus.

Created a gamified system that motivates users to build healthier habits.

What we learned

How to bring AI research into real-world applications.

Best practices for on-device ML and privacy-preserving design.

How to seamlessly integrate third-party SDKs into a cross-platform app.

That productivity tools must combine science + motivation + design to really help users.

What's next for FocusFlow

Expanding focus detection with wearable data (heart rate, biometrics).

Adding community features like team challenges and shared streaks.

Offering richer analytics for long-term productivity patterns.

Exploring partnerships with wellness, education, and workplace platforms.

Built With

• firebase
• onesignal
• openai
• reactnative
• revenuecat
• supabase
• tensorflowlite
• typescript