Querey
The Project
Querey is an AI powered music platform designed to help people intentionally improve their mental and emotional state through sound. Instead of passive scrolling and overstimulating content feeds, Querey uses music, adaptive BPM systems, neuroscience research, and AI coaching to create healthier digital experiences focused on focus, motivation, recovery, relaxation, and emotional balance. The idea came from observing how strongly music affects mood, confidence, energy, and concentration in everyday life. Current music and social media platforms are built primarily for entertainment and retention, but we wanted to explore what technology could look like if it were designed around improving well-being and cognitive performance instead. We were also inspired by research in psychology, sports science, and music therapy showing that rhythm and tempo can influence attention, perceived fatigue, emotional regulation, and productivity. One of Querey’s main features is “Neuro Mode,” an adaptive system that adjusts music selection and BPM ranges depending on the user’s goal or situation. For example, lower BPM ranges support relaxation and sleep preparation, while higher BPM ranges can help increase energy, momentum, and workout intensity. The platform combines Spotify integration with AI to create personalized experiences that feel immersive while still being intentional and healthy. The most difficult part of the project was balancing scientific credibility with a product experience that still feels engaging and modern. We wanted the app to feel as compelling as mainstream platforms without relying on harmful attention-maximizing mechanics. Another challenge was designing the AI coach responsibly so it feels supportive and personalized without overstepping into unrealistic claims. Ultimately, Querey is an attempt to reimagine how music, AI, and behavioral science can work together to create technology that supports human performance and emotional well-being rather than simply competing for attention.
About the team
Team members
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