Attribution infrastructure for AI music
We build intrinsic, block-level attribution for AI-generated and hybrid music. So provenance is traceable, compensation is structured, and rights tracking is not guesswork
What we build
Intrinsic Attribution
Attribution is embedded at generation time, at block level (melody, harmony, stems, motifs, structure).
ISBC
International Standard Sound Block Code, a granular identifier for musical components
BlockDB
A rights-aware database for AI music that connects blocks, usage, and revenue logic
What this enables
Licensing and royalty flows
Easier split calculation, derivative work classification, and audit trails for PROs, publishers and labels. Enables tracking how works influence outputs and making revenue flows auditable in real time, a capability the industry is increasingly demanding.
Metadata and work matching
Bridges ISRC and ISWC, improves registration and reduces mismatch in existing systems. Supports enterprise-focused models that show that robust licensing frameworks are not a theoretical need, but a commercial necessity.
Copyright enforcement and AI detection (in development)
Attribution is the backbone for copyright infringement detection, AI music detection, and bot stream analysis. These are active R&D and pilot topics that build on the same attribution layer.
Whitepaper
Whitepaper on attribution-driven remix licensing and usage-based economic models
LinkContact
Technology and research
Jongpil Lee
CEO
Partnerships and industry (US-Europe)
Virginie Berger
Chief Industry and Rights Officer