Clearception
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Music demo

Make a sample library searchable by sound

Tag and index a large library so you can find material by character rather than filename.

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3 minute walkthrough

The challenge

A large sample library is effectively unsearchable, so the same few sounds get used repeatedly.

The scenario

A producer with tens of thousands of samples wants the right one in seconds rather than twenty minutes.

What goes in

Sample library
The existing collection, however it is organised.

What you can ask

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

  • “Find warm analogue drum breaks around 90 bpm.”
  • “Something darker than this, same groove.”
  • “What have I not used in this project?”

How Clearception approaches it

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

  1. Analyse material

    Observed

    Characterise each sample by its sonic properties.

  2. Index by character

    Observed

    Make the library searchable by how things sound.

  3. Search in words

    AI-inferred

    Resolve plain-language requests against the index.

What you get

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

  • Searchable library

    Material findable by character, tempo and texture.

Why it matters

Less digging
Time goes to arrangement rather than file browsing.
Wider palette
Material you forgot you owned becomes reachable.

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Want to try this with your own work?

Open Music and bring your own data. No signup is needed to read these demos.

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