Lifelong learners and wellness seekers juggle fragmented platforms and generic recommendations that don't match their emotional state. Some apps offer content based on mood, but none brings quotes, book and podcast recommendations, and journal prompts together in one place.

The goal: make identifying emotions intuitive, visually engaging, and scientifically grounded.

I built the experience on Dr. Marc Brackett's Mood Meter framework, organizing 13 emotions with a vibrant color system along an energy scale.

Users identify how they feel through AI analysis of facial expressions or voice tone, or by choosing an emotion manually, then explore mood-matched quotes, books, podcasts, and journal prompts. Journal entries can be added through image, text, or audio.

MindMatch pushed me to map user flows more deliberately than ever, from AI mood detection and multi-modal input to the final recommendation, so each step feels supportive and emotionally aware.

It took far more time than I expected, and it was worth it: a design that balances technical complexity with simplicity, putting both function and human connection first.