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Inspiration
Most productivity tools focus only on tasks, ignoring the human behind them. As a student managing academics and responsibilities, I often felt overwhelmed by rigid to-do lists that didn’t adapt to my mental state.
This led to a key idea:
What if a productivity assistant could understand emotions and adapt accordingly?
DaySavvy was built to bridge the gap between productivity and emotional intelligence, enabling a more sustainable way to work.
What it does
DaySavvy is an emotionally intelligent AI assistant that helps users manage their daily life more effectively.
It allows users to:
Create and manage tasks using natural language Interact via text, voice, or image inputs Automatically extract tasks from unstructured data Get adaptive schedules based on mood and context Receive reminders, insights, and smart suggestions
Instead of static planning, DaySavvy provides a dynamic and personalized productivity experience.
How we built it
DaySavvy is a web-based AI system with a modular architecture.
Frontend: HTML, CSS, JavaScript with Flask (Jinja2 templates) Backend: Python (Flask) with RESTful APIs Database: SQLite with SQLAlchemy ORM AI Layer: Cloud-based LLM for intent detection, emotion analysis, and task extraction Features: FullCalendar (task visualization), Web Speech API (voice input), PWA support Core Logic 𝑓 ( input
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intent + emotion + context f(input)=intent+emotion+context
Output
𝑔 ( intent , emotion , priority ) Output=g(intent,emotion,priority)
This enables the system to convert user input into context-aware and adaptive actions.
Challenges we ran into
Emotion detection accuracy: Interpreting user mood from text required multiple iterations Balancing simplicity vs intelligence: Keeping UI simple while integrating complex AI logic User engagement: Converting visitors into active users is still challenging Solo development constraints: Managing development, testing, and iteration alone
Accomplishments that we're proud of
Built a fully functional AI product from scratch Achieved real user traction (500+ visitors, 146+ signups) Recognized as a top AI project in a university-level exhibition Successfully integrated AI + productivity + emotional intelligence in one platform
What we learned
Building AI products requires both technical and behavioral understanding User experience is as important as AI capability Real-world products face challenges beyond coding, especially retention and usability Iteration and feedback are critical for growth
What's next for DaySavvy
Improve emotion-aware AI and personalization Add voice-based real-time assistance Expand automation and integrations with other platforms Scale infrastructure using cloud technologies Grow the product into a complete AI life assistant
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