Music recommendation is a solved problem, if your goal is keeping someone on the app. Spotify knows exactly what to play to make sure you never leave. That's not discovery — that's a feedback loop optimized for retention.

GrooveFind is built around a different question: what would you find if the algorithm wasn't trying to keep you?

Type anything. The color blue at night. The feeling before a long drive. A book character. A memory you can't place. GrooveFind interprets it the way a person who loves music would: what does that idea actually sound like?

Under the hood: the input goes through an LLM call that extracts musical DNA — texture, mood, tempo, energy, structural feel. That gets mapped to SoundCloud's catalog through a series of targeted searches, then filtered through an algorithm I developed to model how people actually make judgments about musical fit. Not popularity. Not trending. Fit.

The only question I care about: did you like your playlist? Not time-on-app. Not skip rate. Not re-engagement. That's the whole success metric, and it's deliberately hard to game.