MyPart Inc.
Sivan K. Vaknin has a diverse work experience in the technology industry. Sivan started their career as a Software Developer at IDF in 2008, where they worked until 2012. In 2013, they joined Linkury as a Software Developer and stayed with the company until 2018. During this time, they gained valuable experience in software development. In 2018, Sivan moved to MyPart Inc., where they initially worked as a Tech Lead. Later, they were promoted to the role of VP R&D, which they currently hold. Sivan'scontributions have played a crucial role in the success of the company.
Sivan K. Vaknin completed a double major in Psychology and Computer Science, with an emphasis on Brain Science, at the Sagol School of Neuroscience, Tel Aviv University from 2014 to 2017. Prior to that, from 2012 to 2014, Sivan attended Rimon School of Jazz and Contemporary Music, although no specific degree or field of study was mentioned.
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MyPart Inc.
MyPart is an AI-powered song search and matching platform for anyone in pursuit of songs, including the music industry, TV/Film and advertising.For Music and Creative Executives:MyPart’s award-winning technology uses reference songs- rather than conventional “tagging” techniques- to help A&Rs, Sync, and Music Supervisors “dig” throughand 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 featuresA 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