Search music by meaning
Describe what you need: a scene, a feeling, a reference. The search talks it through with you.
Enter to send · Shift+Enter for line break
You know the brief. Not the track.
That's where CMI starts: the search asks back, you refine, and the right track surfaces in a few exchanges. A conversation, not a search form, and faster than guessing the tags a system wants.
That conversation only works because of what sits underneath. Every track in your catalog is described in detail by meaning, not tags, across four dimensions: what the music does, what it evokes, where it belongs, which moments it can carry. A scene speaks the same language.
By the end, you've found the scene's track, often a deep cut rather than the obvious hit. Dig deeper, decide faster.
Bring more of your catalog into play.
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Tuned to a trained ear
Conversational search is suddenly everywhere, but off-the-shelf LLMs cannot describe music reliably. Our architecture grounds the search in a musicological method, so users get results that make sense musically, not just statistically.
First the demo, then your catalog
Start with this public demo, built on a reference corpus of 40,000 tracks (CC-BY). Then test CMI on your own catalog. That's where you see what your catalog can really do and where each track belongs.
Data stays with us
You can entrust CMI with confidential briefings. Your inputs and catalog stay private: never used to train a model, never sent to OpenAI, Google, or any external cloud, and held on our own servers under tight access control.
API access
Integrate CMI intelligence into your own tools, applications and workflows across catalog search, sync portals, licensing platforms, archives and client-facing discovery layers. Access on request.