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Onboarding
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Time frame addition window
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Home Page
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Task Calendar
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Add fixed schedule
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Profile page
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Analytics page
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Add weekly tasks
Inspiration
Traditional productivity apps treat everyone the same. We wanted to build something more human — a system that understands behavior, energy levels, habits, and motivation patterns instead of just managing tasks. Darpan was inspired by the idea of creating an “AI twin” that reflects your lifestyle and helps you work smarter, not harder.
What it does
Darpan is an AI-powered productivity planner that adapts to the user’s habits, routines, and mental state. It intelligently schedules tasks, predicts burnout patterns, analyzes productivity trends, and provides personalized recommendations to improve focus and consistency. The app also integrates health and activity data to better understand user behavior and optimize planning.
How we built it
We built Darpan using Flutter for a cross-platform mobile experience and Firebase for backend services like authentication, cloud storage, and real-time database support. The AI and ML pipeline processes user activity, productivity metrics, and wellness data to generate adaptive schedules and predictive insights. We also automated data syncing and preprocessing pipelines to reduce manual intervention.
Challenges we ran into
One of the biggest challenges was designing a system that combines productivity data with behavioral and wellness insights meaningfully. Building automated pipelines for importing and processing external data was also complex. Another challenge was balancing intelligent automation with user control so the app feels supportive rather than intrusive.
Accomplishments that we're proud of
We successfully created a working AI-driven productivity ecosystem instead of just another task manager. We are proud of integrating adaptive planning, predictive analytics, and wellness-aware scheduling into a single platform. We also built scalable backend workflows and a clean, modern cross-platform UI.
What we learned
We learned how difficult — and important — it is to design AI systems around human behavior. The project improved our understanding of Flutter architecture, cloud-based app development, automation pipelines, and practical machine learning integration. We also learned how crucial personalization is for long-term user engagement.
What's next for Darpan
We plan to improve the behavioral AI models with deeper personalization and real-time adaptation. Future updates include voice interaction, smarter burnout detection, calendar/email integration, wearable device support, and collaborative productivity features. Our long-term vision is to make Darpan a true AI productivity companion that evolves with the user over time.
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