For Rights Organizations
Attribution Evidence for PROs and Publishers
The right data at the right time. Musical AI delivers structured attribution output that integrates with your existing royalty infrastructure, so you are ready when AI attribution claims become operational.
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Why Act Now
The Attribution Gap Is Widening
Every week, generative AI platforms produce music trained on recorded catalog. The organizations with provenance data in hand when regulatory and litigation clarity arrives will be positioned to act first. Those without it will be building infrastructure under pressure.
Regulatory Readiness
EU AI Act transparency requirements and pending US legislation are moving toward training-data disclosure. Build the evidentiary record now.
Stronger Negotiating Position
Publishers with structured attribution data have a factual basis in training-license negotiations that those without it do not. Documented provenance is the difference between a claim and a supported claim.
Retroactive Claim Support
Attribution queries run against historical AI output, not just new generations. Start building a provenance record that covers past use.
For Performing Rights Organizations
Built to Fit Your Existing Royalty Infrastructure
Index your ISRC catalog
Submit your catalog via bulk ingest. ISRC keys, rights-holder trees, and audio references are indexed for continuous attribution matching.
Submit AI-generated tracks for attribution
When AI platforms provide generated-audio samples, submit them to the attribution endpoint. Results arrive in milliseconds with ranked ISRC matches and confidence scores.
Route results into distribution workflows
Attribution responses are structured as ISRC-keyed JSON, compatible with standard royalty distribution data schemas. No custom integration work required.
Attribution response structure
{
"isrc": "USAT22304812",
"score": 0.87,
"rights_holder": "Meridian Songs LLC",
"stem_match": "vocal_lead"
},
{
"isrc": "GBAYE9800301",
"score": 0.61,
"rights_holder": "Coastline Music Ltd",
"stem_match": "harmonic"
}
]
For Music Publishers
Catalog Data Quality Determines Attribution Speed
Publishers with clean ISRC data, complete rights-holder trees, and high-quality audio references get faster, higher-confidence attribution results. Musical AI works with whatever catalog structure you have and flags gaps that would reduce attribution precision.
Catalog Health Diagnostics
Before indexing, Musical AI runs a catalog health check identifying missing ISRC assignments, duplicate entries, and incomplete rights-holder coverage that would reduce attribution precision.
Ongoing Monitoring
Set up continuous monitoring against a list of AI-platform output URLs or bulk audio uploads. Receive attribution reports on a schedule that fits your operational cadence.
Position Your Organization for AI Attribution
Request access to the Musical AI API and begin building provenance data before the first attribution claims land on your desk.