Moodora

Emotion tracking page
Log in page
Mood card
Mood card animation
Support Card

Inspiration

We noticed that many people experience emotions physically before they can name them, like tears without warning, a tight chest, or constant fatigue. Often, these are emotional signals that go unseen or unprocessed in a fast-paced world. We wanted to create a gentle space where emotions can be acknowledged, not judged, especially when words are hard to find.

What it does

Moodora helps users tune into their emotional state through three guided steps:
feel, notice, and record.

Instead of typing or choosing from complex emotion lists, users select from non-verbal metaphors — like mist, fireballs, or clouds — to represent their current mood.
Each choice generates a supportive phrase using AI, and builds a personal mood library that reflects patterns over time.

How we built it

Frontend: React + TypeScript, Vite for a lightweight build setup
Styling: Tailwind CSS, with custom components and soft gradient theming
Animations: Breath-orb component to support emotional centering
Backend: Supabase for user auth, emotion log storage, and real-time data
AI Integration: OpenAI GPT API to generate gentle, metaphor-based support language
Deployed on: Netlify

Challenges we ran into

Designing a breathing experience that feels slow enough, but not frustrating
Tuning the AI prompts to generate emotionally accurate and comforting language
Balancing visual clarity with softness - making something calm, but not bland
Structuring the emotional data in a way that feels personal, not clinical

Accomplishments that we're proud of

Creating a fully working emotion tracking flow in just a few weeks
Building a metaphor system that allows people to express themselves without pressure
Received a lot of positive feedback from beta users

What we learned

Emotions don't always need words, metaphor and rhythm can speak more deeply
Gentle UI matters: microcopy, spacing, and timing all affect emotional safety
Even a minimal app can create impact when it's rooted in empathy

What's next for Moodora

Add breathing session analytics (e.g. time spent, self-reported clarity after)
Introduce emotion-based soundscapes as ambient support
Introduce an AI assistant that offers gentle, actionable suggestions based on users’ emotional states
Allow users to save helpful suggestion cards for future reference
Enable mood card sharing and export options to support reflection or conversation with others