About
Music done right.
A small company, a large catalog, and proprietary AI. Made in Madrid, built to sound right wherever you play it.
The story
Started with a party that sounded wrong.
I started BeethovenBeat — I’m Fuad — in April 2026. The idea was simple: it pissed me off to spend 30 minutes before every party picking music that ended up sounding wrong 10 minutes in because nothing adapted to the shifting mood.
I’m one person. Not a team of 20. Not a Series A startup. I build this with Claude Code (Anthropic), with music-specialized AI models (MERT, CLAP), and with 500 DJ sessions I curated myself as reference for “how a good session should flow”.
Transparency matters: this website is honest about what we are today. Indie, small, growing. And with AI that works.
Mission
Democratize quality music curation. For everyone.
So your neighborhood bar can sound as good as the trendy bar in Barcelona. So your house party doesn't sound worse than an expensive wedding. So retail stores stop paying Spotify + SGAE for mediocre music.
Values
Five non-negotiables.
- 01
Honest with the client
If our product doesn't fit your need, we'll tell you. We don't sell vaporware.
- 02
Curated, not scraped
6,926-track catalog that passes real quality filters. Not 10 million uncurated.
- 03
Fewer features, better execution
We'd rather do 3 things brilliantly than 20 mediocrely.
- 04
Local and global
Built in Madrid with international lens. ES+EN from day one.
- 05
No locks
No annual contracts. No vendor lock-in. If you leave, you leave clean.
Technology
Proprietary AI. Not a ChatGPT wrapper.
We build proprietary three-level reinforcement learning (DRL) architecture, specific to musical decisions. We don't sell anything we can't execute.
- MERT-330M music embeddings (audio representation)
- CLAP text-audio alignment (understanding descriptions)
- PPO + SAC hierarchical DRL (DJ decisions)
- Camelot wheel + BPM matching (harmonic transitions)
- 500 real DJ sessions as training data
- Real GPU RTX 4090 cloud training — not theoretical