Music rights holders often struggle to identify and monetize user-generated content (UGC) that incorporates their copyrighted material across various social and sharing platforms. Much of this content is difficult to detect using traditional methods, leading to unclaimed royalties and lost revenue for artists and publishers.

Song Sleuth offers a technology platform that leverages machine learning to identify hard-to-detect UGC across major social media and content-sharing platforms. Their proprietary UGSeeker technology finds previously undiscoverable instances of copyrighted music being used in user-created videos and other content. By uncovering this "unfindable" content, Song Sleuth enables music rights owners to claim royalties that would otherwise go unclaimed. The platform provides a comprehensive solution for rights holders to track and monetize the use of their music in the expanding landscape of user-generated content.

Machine-learning algorithms specifically trained to identify copyrighted music within UGC.

UGSeeker technology designed to find content that is difficult for traditional methods to detect.

Comprehensive coverage of major social and sharing platforms.

Royalty claim processing and reporting tools for rights holders.

Song Sleuth's primary customers are music rights holders, including artists, publishers, and record labels, who are seeking to maximize their royalty revenue from user-generated content.