WavNav is an audio sample explorer built to make large sample libraries easier to navigate. Instead of digging through folders and filenames, it maps sounds into a 2D visual space where similar samples sit near each other, so browsing becomes much more like exploring a map than managing files.

If you want the full product overview, check out the WavNav product page first. It is much more in depth than this post and covers the app in its proper context.

The project sits at the intersection of audio analysis, machine learning, and music production tooling. The current version focuses on fast local analysis, visual search, and practical studio workflows for producers working with big libraries.

WavNav demo preview Demo · click to play
A walkthrough of WavNav — browsing an audio sample library as a 2D map, previewing samples on hover, and finding similar sounds through semantic search.

What it does

  • Visual browser: samples appear as points on a map, with similar sounds clustering together.
  • Semantic search: search for sounds using text prompts like "snare", "bright pluck", or "dark pad".
  • Search by sound: drop a sample into the app to find similar material in your library.
  • Key and BPM filters: narrow results by musical key, tempo, or both.
  • Folder management: add multiple sample folders and toggle them on or off without rebuilding everything from scratch.
  • Local-first workflow: machine learning models and audio processing run on your own machine, and the site copy describes the product as fully local with no cloud uploads or data collection after download.

Workflow

WavNav is built around quick sample discovery:

  • pan and zoom around the map to explore dense libraries visually
  • hover to preview sounds
  • click or inspect samples while searching
  • copy file paths directly for use in a DAW
  • open files in Finder from the app
  • save folders and settings between sessions
  • use right-click similarity search to find nearby alternatives

Performance and scale

WavNav is made for large-library use:

  • built for 50,000+ samples
  • about ~1 minute for a first load of a 50k library
  • about <3s startup from cache
  • 60fps navigation target
  • GPU-accelerated rendering via OpenGL/Metal
  • clustering and map-based exploration using audio embeddings and UMAP-style visualisation

Platform status

  • macOS: supported on Intel and Apple Silicon, with a stated minimum of macOS 13.0
  • Windows: supported in beta, x86 only, with a minimum of Windows 10 version 1803
Screenshot Screenshot

Product page • Features • Screenshots • Buy WavNav