Vybe – Because dead parties aren’t an option.

vybe-logo

Inspiration

Student life is a cycle of classes, assignments, and late-night study sessions. Parties 🎉 are a chance to destress, bond, and recharge. But nothing ruins the night faster than bad music. Vybe gives DJs real-time feedback on how the crowd feels to keep the energy just right.

What it does

Vybe analyzes crowd movement 💃🕺 and energy to generate a “Vibe Score”. Using this, it recommends tracks that match or lift the mood—helping DJs create unforgettable student parties.

How we built it

Frontend: Built with Next.js and TypeScript for a fast, responsive DJ and Audience Dashboard.
Backend: Python services running on Lambda, with APIs through Amazon API Gateway.
Data & Storage: User interaction and engagement data stored in Amazon DynamoDB.
Analysis: Real-time computer vision powered by OpenCV to detect movement/facial expressions.
AI Layer: Used Groq for handling fast inference and recommendation logic.

Challenges we ran into

Processing real-time vision data without lag
Converting raw inputs into a clear, useful Vibe Score
Designing a simple UI DJs could read at a glance
Pulling multiple tech stacks together under hackathon deadlines

Accomplishments that we're proud of

Built a fully working DJ dashboard + audience voting system in just one hackathon.
Successfully created a Vibe Score metric that combines movement and energy.
Made something that students can immediately relate to and see in action.
Bridged the gap between tech and nightlife in a creative way.