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We provide the missing infrastructure for attribution at scale.

Musical AI delivers transparent, auditable attribution infrastructure that connects generative music systems to real licensing outcomes. Our platform fits into existing licensing agreements and delivers the records and reporting companies need to operate with confidence.

This is infrastructure,
not experimentation.

Rights Holders

Rights holders want to participate in AI revenue opportunities while maintaining control over their creative works and ensuring fair compensation for their contributions.

AI Companies

AI companies need vast amounts of licensed music for training, but navigating individual rights clearances is complex, time-consuming, and filled with legal challenges.

Rights Holders

Rights holders want to participate in AI revenue opportunities while maintaining control over their creative works and ensuring fair compensation for their contributions.

AI Companies

AI companies need vast amounts of licensed music for training, but navigating individual rights clearances is complex, time-consuming, and filled with legal challenges.

Our Role:

Independent, Closed‑Loop Attribution

Generative music changed everything about how creative outputs get made. But the rights systems we have were built for known works, not statistical influence.

AI companies today need clear influence measurement, defensible attribution, and compliance that actually scales. Legacy detection tools weren't designed for this.

Proportional, output-level attribution is the solution.

Musical AI provides the missing infrastructure that connects these needs.

We solve the complexity of generative AI rights management, licensing agreements, and compliance requirements, through our proprietary attribution tracking technology, enabling both sides to focus on what they do best.

Connect with us about Attribution

Let's Talk Attribution

Scale & Validation

Musical AI is operating infrastructure that supports real licensing and enterprise use cases.

FairlyTrained.org certification

for transparency and ethical practices

Patent-pending attribution technology

that underpins production-grade usage

Regulatory alignment

with emerging frameworks like the EU AI Act and California AB 2013

Leadership Team

Sean Power

Chief Executive Officer

Seasoned founder and operator with enterprise and music tech experience. Former CEO & co-founder at Repable. Alum: CoTweet (acquired by Salesforce.com), PostRank (acquired by Google), Coradiant (acquired by BMC), Dishcrawl (Sold to Culinary Events) & MTV Europe. Published Author (O’Reilly Media), Techstars AI Mentor & Musician.

Matthew Adell

Chief Operating Officer

Veteran product and music leader with a track record of building and scaling music platforms. Former - VP Music and Product at MusicNow (Sold to AOL), VP Music and Product at Napster (Sold to Best Buy), CEO at Beatport (Sold to SFX), CEO & Founder at MetaPop (Sold to Native Instruments). Techstars Music Mentor & Musician.

Nicolas Gonzalez Thomas

Chief Technology Officer

Technical lead with expertise in machine learning, music computational creativity, and scalable systems. Master’s Degree, Machine Learning and Music Computational Creativity at Simon Fraser University. Research assistant in Interactive Music Generation at Simon Fraser University. Techstars AI Alumnus & Musician.

Advisors

Vickie Nauman

Strategic Advisor

Influential Music Tech advisor (Spotify, Meta, Sonos, Riot Games); Successful startup exits including Beat Saber/Oculus and 7digital/Songtradr.

Liz Moody

Strategic Advisor

Partner and Chair of New Media Group, Granderson des Rochers, LLP; Digital media pioneer; Former YouTube and Pandora exec.

We are attribution infrastructure powering AI training data licensing

Mission

We're building attribution into a reliable, enterprise-grade layer for generative media.

That means infrastructure that scales with real commercial volumes, produces reliable, defensible attribution, and fits the licensing frameworks businesses already use.

Everything we design and prioritize flows from that.

We're building attribution into a reliable, enterprise-grade layer for generative media.

That means infrastructure that scales with real commercial volumes, produces reliable, defensible attribution, and fits the licensing frameworks businesses already use.

Everything we design and prioritize flows from that.

Vision

We envision a future where generative music companies can innovate without unresolved risk, and where rights and influence are measured clearly and consistently.

Attribution should be systemic, not an afterthought.

We envision a future where generative music companies can innovate without unresolved risk, and where rights and influence are measured clearly and consistently.

Attribution should be systemic, not an afterthought.