Training Provenance API

Know Which Recordings Trained Every AI Track You License

Musical AI gives PROs and publishers an API that traces training data provenance in AI-generated music and routes the correct royalty split to the right rights holders.

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The Attribution Gap

Generative AI Is Built on Recorded Music. Rights Holders Have No Visibility.

When a model learns to compose from thousands of tracks, the recordings that shaped it generate no royalties under existing structures. Musical AI builds the attribution layer that makes those contributions trackable.

Spectral Fingerprinting

Decompose generated audio into constituent frequency signatures and match them against catalog recordings with sub-second latency.

Provenance Tracing

Follow the training data chain from the generated output back to specific recordings, returning confidence scores and ISRC identifiers.

Rights-Ready Output

Every attribution response is structured for downstream royalty workflows, compatible with existing PRO and publisher data systems.

Built for Rights Infrastructure

A Single API Endpoint, Integrated Into Your Existing Workflow

Submit any AI-generated audio. Get attribution evidence back.

The Musical AI API accepts a WAV or MP3 URL, runs multi-layer source-separation and spectral analysis, and returns a ranked list of recordings from your catalog that influenced the output, complete with match confidence scores and rights metadata.

View API Reference
attribution_request.py 
import requests

response = requests.post(
    "https://api.wearemuiscalai.com/v1/attribute",
    headers={"Authorization": f"Bearer {API_KEY}"},
    json={
        "audio_url": "https://storage.example.com/ai-track.wav",
        "catalog_id": "cat_pro_northwest_01",
        "threshold": 0.40
    }
)

data = response.json()
# data["matches"][0]["isrc"]  → "USAT22304812"
# data["matches"][0]["score"] → 0.87

Who We Serve

Designed for the Organizations That Manage Rights at Scale

Performing Rights Organizations

PROs need an attribution infrastructure that fits into existing royalty distribution workflows. Musical AI delivers structured evidence compatible with ISRC-based reporting, with no changes required to downstream systems.

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Music Publishers

Publishers with well-catalogued ISRC and ownership data can submit catalog segments and receive ongoing attribution monitoring as AI platforms generate new music. Early visibility means earlier claims.

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Why It Matters Now

The Legal and Technical Landscape Is Moving Fast

EU AI Act transparency requirements. ASCAP and BMI fielding training-consent questions. The Mechanical Licensing Collective navigating an attribution gap its infrastructure was not built for. Musical AI positions your organization to act when the first wave of AI attribution claims arrives.

3.5B+
Tracks estimated used in AI training globally (industry analysis)
$0
Training royalties distributed under current collection structures
2024
Year Musical AI was founded to close this attribution gap

Start Building Your Attribution Record

Request early access to the Musical AI API and begin cataloguing provenance data before the regulatory and litigation landscape solidifies.

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