and prioritize their musical catalogs and/or discover new talent. This helps these industry decision-makers find songs that share common harmonic, melodic, lyrical, sonic and structural features with their predefined benchmarks, and ensures they only listen to the “right” songs that actually match their needs.

For Songwriters: MyPart’s AI analyzes songs submitted by emerging songwriters from all over the world, in order to place them with opportunities in the Music, TV/Film and Advertising Industries. We believe your songs deserve a shot, and create matches purely based on song relevance, rather than personal connections or industry access.

MyPart graduated from Universal Music's exclusive Abbey Road RED program in London and Capitol Records' gBeta program in LA, as well as Deloitte's LaunchPad Growth program, and won the MassChallenge 2018 gold award and Music Week 2021 Tech Summit.

Its proprietary 'Song Mining' engine conducts comprehensive and granular analysis of lyrical, musical and sonic relevance based on a wide technology stack that combines machine learning, computational linguistics, and digital signal processing to determine the likely relevance of any song to any set of reference songs.

Our unique approach combines two key qualities: The ability to search for songs with a set of reference songs We created a song fingerprinting technique that abstracts song DNA to enable searching for songs with reference songs, based on common harmonic, melodic, lyrical, sonic and structural features A distinct focus on the semantics and aesthetics of song lyrics. At the heart of our distinct approach is a special focus on the deep comprehension of song lyrics