Find the track you own by describing it

The challenge

The right track is in the library somewhere, but its title is gone and scrolling crates mid-set takes longer than the current record has left.

The scenario

A DJ two hours into a club set wants something dark and rolling around 126 BPM that they have not played this year, from a library spread across Serato and an old rekordbox collection.

What you can ask

Illustrative prompts. Results depend on your own data and are not deterministic.

• “Dark rolling tech house around 126 BPM that I haven't played this year.”Copy
• “Vocal disco edits in A minor or compatible keys.”Copy

How Clearception approaches it

How the work is structured. Each step shows what its output is grounded in.

1. 1

   Read the sentence as filters

   AI-inferred

   BPM range, mood words, genre and history become typed filters you can see and edit.

2. 2

   Search the local index

   Observed

   Every connected library is searched on the DJ's computer, offline.

3. 3

   Rank with reasons

   Observed

   Results show which filter each track matched and when it was last played.

What you get

The shape of what comes back — not a promised result.

• A ranked track list

  Matching tracks from every connected library, with BPM, key, crate and last-played date.

Why it matters

Seconds, not scrolling

One search across every library instead of crate by crate.

Nothing uploaded

The library is searched where it lives.