RaagaPay is the rights-cleared training-data layer for music AI. We license expert-annotated audio directly from the maestros who hold the tradition, with a consent and royalty trail on every track, built DPDP Act- and EU AI Act-ready.

We start with Indian classical, the world's hardest tradition to fake and the one today's models misread most: a 40%+ error rate on the microtonal raga and complex tala that Western 12-tone systems cannot parse. Roughly half of our corpus also maps the ragas behind Hindi film music, linking 5,000 years of classical theory to the Bollywood catalogue the world already knows.

What makes the data an asset, not just a recording:
Licensed at the source. Direct maestro agreements, 100% consent-logged. The legitimate way to acquire music that cannot be legally scraped.
Annotated by experts. An 80-point framework encoding raga, gharana, tala, and Shruti into machine-readable JSON no model can invent, with reasoning traces for ground-truth MIR.

Built to standard. Studio-grade multi-stem audio and FAIR-compliant metadata, delivered by enterprise API.
Artist-first by design. Maestros are research partners, not data sources: full autonomy, data sovereignty, and transparent lifetime royalties on every use.

For AI labs and data teams: a clean, rights-clean foundation for culturally intelligent models. For maestros and institutions: a fair way to preserve and be paid for a vanishing tradition. 


RaagaPay

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RaagaPay

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