Start with one segment of the catalog. Match works against registries and surface unclaimed royalties; prove a recovery
There's money owed to our catalog sitting unclaimed because
You can scan one catalog segment for unmatched royalties without overhauling your admin.
What changes when AI orchestration runs the loop
Not 'better matching' -> 'recover the black-box royalties your current matching can't resolve.'
You've tried matching tools; the hard, fragmented registrations defeat them. A model that resolves linked works/splits across agencies recovers what generic matching leaves unmatched.
Not 'more royalty automation' -> 'clear the matching exceptions your platform kicks back.'
You've got a royalty platform; data normalization and matching exceptions stay manual. A model trained on your reconciliation decisions clears the matches and flags real exceptions.
Not 'more calculation' -> 'prove the statements are accurate when a society audits.'
You calculate; proving accuracy for an audit stays manual. We evidence statement accuracy continuously - though royalty's bigger Empromptu wins are statement-processing throughput and black-box recovery.
Not 'more calculation' -> 'explain why a number is what it is, traced to source.'
You calculate; explaining a discrepancy to a rights-holder is manual. A model trained on your data relationships traces a questioned figure across statements, contracts, and splits and shows its work.
Not 'more outreach' -> 'win rosters with the recovery results that prove your value.'
You've tried outreach; rosters are won on demonstrated recovery. We pair BD targeting with the recovery proof that closes rights-holders.
Where the work changes
Five frames in this vertical's language — leak, operational, governance, analysis, growth.
Leak / value-capture: Not 'better matching' -> 'recover the black-box royalties your current matching
There's money owed to our catalog sitting unclaimed because the metadata never matched.
- Metadata chaos, registration gaps, siloed systems leave royalties unmatched.
- Black-box pool: unidentified royalties held then redistributed to incumbents after a holding period (use-it-or-lose-it).
- Underreported statements: incorrect splits, mis-tagged works, misapplied legacy formulas.
- Per-instance amounts small; only systematic matching at scale makes recovery economic.
Operational throughput: Not 'more royalty automation' -> 'clear the matching exceptions your platform ki
Every statement cycle we hand-import DSP reports, reconcile them, and calculate splits across spreadsheets.
- Manually importing DSP statements, reconciling reports, calculating splits by hand each cycle.
- Volume of micro-payments, fractional rights, and real-time consumption data overwhelms legacy/manual processing.
- Matching/validating/reconciling across multiple sources is the core labor sink.
- Statements delivered weeks/months late erode rights-holder trust.
Governance & audit: Not 'more calculation' -> 'prove the statements are accurate when a society audi
There's real compliance - statutory-license terms, CRB statements-of-account, audit rights - but it's a niche regime, not a bank-grade exam.
- Real compliance: statutory-license terms, Copyright Royalty Board statements-of-account, SoundExchange/PRO audit rights, statement accuracy.
- Rights-holders and societies hold audit rights; inaccurate statements are the exposure.
- Proof of accurate, complete statements is genuine but a niche regime.
- Compliance and accuracy tie back to the leak/recovery story (correct money to the right party).
Analysis / diagnosis: Not 'more calculation' -> 'explain why a number is what it is, traced to source.
When a royalty number looks wrong, diagnosing why means tracing it back across DSP statements, contracts, and splits that all arrive in different formats.
- DSP statements (Spotify, Apple, etc.) arrive in different formats; fractional rights and micro-payments multiply the matching problem.
- Diagnosing a discrepancy means tracing a payment back across statements, contract terms, and split logic.
- Volume of micro-payments has overwhelmed legacy systems - errors are common and hard to localize.
- Rights-holders dispute statements; the admin must explain why a number is what it is, traced to source.
Growth / outcome: Not 'more outreach' -> 'win rosters with the recovery results that prove your va
Our 'growth' is signing catalogs and rights-holders to administer - it's BD, but the core service is recovery.
- For PROs/admins/publishers, growth = signing catalogs and rights-holders; for rights-holders, the story is the leak engine (black-box recovery).
- Roster/BD outreach is relationship-bound and under-systematized.
- Acquisition competes on demonstrated recovery track record (which ties back to the leak engine).
- Limited public Growth benchmarks for this niche.
Where current tooling falls short
Category limitation: the collection infrastructure holds the money but identification depends on matching that historically can't reconcile messy/missing registrations at scale; the recovery judgment (claim, correct, register) is fragmented across agencies. This is a linked-object/entity-resolution
What's leaking and what it costs
Frequently asked
Still have questions?
Book a 25-min callThere's real compliance - statutory-license terms, CRB statements-of-account, audit rights - but it's a niche regime, not a bank-grade exam. Not 'more calculation' -> 'prove the statements are accurate when a society audits.'