Recognition is one endpoint. Here is what you can build on it.
Every one of these ships on top of a single call to POST /v1/tracks/identify. Identify the recording, then use the id to pull in whatever metadata the product needs.
For a venue screen, DJ software, or a personal listening-history app: fingerprint whatever is playing and log the exact recording, timestamped, with its ISRC.
POST /v1/tracks/identifyIdentify tracks inside recorded episodes, or point stream monitoring at a live broadcast and build a continuous spin log with the ISRC and label a report of use needs.
Identify + stream monitoringLet users identify a track from a short recording, then resolve it to a clean title, its ISRC, and buy/listen links on Beatport, Spotify, and Apple Music.
Identify + cross-platform linksOn a UGC or creator platform, detect the recording behind a video or voice memo and attach its ISRC so rights and reporting are handled from the moment of upload.
Identify then GET /v1/tracks/:idIdentify the recording in a sample, then cross to its ISRC and the ISWC composition behind it to start the clearance conversation with the right rights holders.
Identify + ISWC lookupRecognise what a user is listening to or watching and surface metadata, context, or related links in real time, without asking them to type anything.
POST /v1/tracks/identifyFrom audio to a track id in three steps
You bring the audio; we bring the catalog and do the matching.
- 1
Fingerprint on the device, or upload
Run Chromaprint's fpcalc -raw client-side and send a ~1 KB integer array, so no audio ever leaves the device. Or POST the raw file and we fingerprint it for you. Same endpoint, same response.
- 2
We match 90M+ recordings
Your fingerprint is matched against an acoustic index spanning the whole catalog, robust to bitrate, format, and encoding differences.
- 3
Get an id + confidence, then hydrate
You get ranked matches, each slim: id, title, artists, and a 0 to 1 confidence score. Look the winner up by id for its ISRC, genre, label, release date, and cross-platform IDs.
One POST, in your language
The recommended path: fingerprint with Chromaprint's fpcalc client-side and send the integer array. Nothing but a ~1 KB fingerprint leaves the device.
# Fingerprint on the device, no audio leaves itfpcalc -raw -length 30 track.mp3 # -> FINGERPRINT=1684564321,-1109695284,...curl -X POST https://api.sonovault.now/v1/tracks/identify \-H "x-api-key: YOUR_API_KEY" \-H "Content-Type: application/json" \-d '{"fingerprint":[1684564321,-1109695284,1085316]}'
Prefer not to run fpcalc? Send the raw file and we fingerprint it server-side (up to 100 MB, any ffmpeg-decodable format).
# No fpcalc? POST the raw file and we fingerprint it server-side.# Whole file is the reliable choice; 128 kbps is plenty (320/lossless just costs more).curl -X POST https://api.sonovault.now/v1/tracks/identify \-H "x-api-key: YOUR_API_KEY" \-H "Content-Type: application/octet-stream" \--data-binary @track.mp3
The response is deliberately small: a ranked results array, best match first, each with a confidence score. Hydrate the winner by id for ISRC, genre, and cross-platform links.
{"matched": true,"results": [{"id": 123,"title": "One More Time","artists": [{ "id": 9001, "name": "Daft Punk", "is_primary": true }],"confidence": 0.98}],"credits_charged": 10}
The recognition, without the infrastructure
Rolling your own means building an acoustic index over tens of millions of tracks, then wiring up every metadata source separately. This is that, minus the months.
The hard part of recognition is the 90M+ acoustic index and keeping it current. That is hosted for you. You send a fingerprint and get a match, with nothing to train, store, or scale.
A single x-api-key. No token refresh, no per-platform integration, and no commercial-use approval queue to clear before you can ship.
Match client-side with fpcalc (private, ~1 KB) or hand us the file and skip the tooling. Both hit the same endpoint and return the same shape.
Every hit resolves to ISRC, genre, label, release date, and IDs on Spotify, Apple Music, Tidal, Beatport, Discogs, and MusicBrainz, so recognition feeds straight into the rest of your product.
| Aspect | Roll your own | With SonoVault |
|---|---|---|
| Reference catalog | Assemble and fingerprint tens of millions of tracks yourself. | 90M+ recordings already indexed and updated daily. |
| Fingerprinting | Stand up Chromaprint / an index and tune matching. | One POST; fingerprint client-side or let us do it. |
| Metadata after a match | Wire up Spotify, Apple, Discogs, MusicBrainz separately. | ISRC, label, genre, and every platform ID in one lookup. |
| Access | Per-platform OAuth, tokens, and approval reviews. | One x-api-key, free tier, self-serve. |
| Time to first match | Weeks of infrastructure before a single result. | Minutes: sign up, send a fingerprint, read the id. |
Want the full technical rundown of the endpoint, from fingerprint formats to retry behaviour? The audio recognition reference has it, and the API docs cover every route you would hydrate a match with.
Pricing and data notes
Frequently asked questions
Start building with audio recognition
Create a free account, grab a key, and send your first fingerprint straight away. No approval queue, no index to maintain.