About Musical AI
Building the Attribution Layer Music Rights Needed Yesterday
Founded in 2024 in West Hollywood, Musical AI was built to solve a specific infrastructure gap: the absence of provenance data connecting AI-generated music back to the recordings that shaped it.
Our View
The rights framework for AI training is being written right now
The legal and regulatory landscape around AI training data is in active formation. Every week, court decisions, regulatory guidance, and legislative drafts move the boundaries. The organizations that arrive at clarity with attribution data already in hand will be positioned to enforce their rights. Those that wait until the framework is final will be building infrastructure under pressure.
Musical AI was founded on the view that the window to build a proactive provenance record is now, not after the first enforcement actions. We build tools for the organizations that manage music rights at scale, designed to fit into the workflows and data standards they already operate.
Company facts
- Founded
- 2024
- Headquarters
- 8560 West Sunset Boulevard, Suite 500, West Hollywood, CA 90069
- Funding
- Angel round, September 2025
- Contact
- [email protected]
The Team
Built by People Who Understand Both Music Rights and Machine Learning
Sean Power
CEO and Co-Founder
Sean's background is in music rights strategy and the data infrastructure that rights organizations rely on. He saw the training-provenance gap forming as generative AI music tools proliferated and founded Musical AI in 2024 to build the layer that makes those contributions trackable.
Maya Hendricks
CTO and Co-Founder
Maya's focus is audio signal processing, music information retrieval, and source-separation system design. She built the attribution pipeline architecture at the core of what Musical AI does, applying years of work on frequency-domain analysis problems to the training-provenance challenge.
James Adeyemi
Head of Rights Partnerships
James brings deep knowledge of how music licensing and rights administration actually works inside PROs and publisher catalogs. His focus is translating that institutional knowledge into the partner relationships and workflow integrations Musical AI needs to be useful to the organizations we serve.
Our Approach
Infrastructure First, Not Another Analytics Dashboard
Musical AI is built as infrastructure, not a reporting tool. The API is designed to slot into existing royalty distribution pipelines, return ISRC-keyed data your systems already understand, and require no custom integration work from your data engineering team.
ISRC-Native Output
Every attribution result is keyed to ISRC identifiers, the standard your royalty systems already use. No translation layer required between our API and your distribution workflow.
Evidentiary Quality
Attribution results include confidence scores, stem-level match detail, and a full audit trail export. The output is structured for legal and compliance review, not just internal dashboards.
Catalog Privacy
Your catalog data is your data. Isolated namespaces at the storage layer, not just access-control policies. We do not use client catalog data for model training or cross-client analysis.
Work With Us
Request API access or reach out to discuss your organization's attribution requirements directly with the team.