"Today we have streams and NFTs. Music management, however, hasn’t changed much behind the scenes" - Fedor Terekhov

"Today we have streams and NFTs. Music management, however, hasn’t changed much behind the scenes" - Fedor Terekhov


Helga.works is the revolutionary AI music manager that changes everything. It has set out to bring artists and managers to the next level, enabling them to become more data-driven, efficient, and be paid for what is owed. In an interview with ArtistConnect, Fedor Terekhov (Co-Founder & CTO) talks about the idea and vision of Helga.works.


How did you come up with the idea of Helga.works? What problem does Helga.works solve?

Fedor: Vincenzo has more than six years of experience as a music manager for multiple artists. He realized more than a full-time job with a heavy workload is necessary to learn and perform state-of-the-art management and the controlling of pay sources, rights, revenues, and usage data. Taking valuable time away from other core commitments. To solve this problem, Vincenzo and I developed Helga.works, an AI music manager for music professionals worldwide to ensure, they are getting paid for what is owed.

What is the vision of Helga.works?

Fedor: A hundred years ago, music was played on piano rolls; today we have streams and NFTs. Music management, however, hasn’t changed much behind the scenes. Running a successful career in the 21st century will be a coexistence between traditional artist management and new technologies. The vision of Helga.works is to support the transition to this new era and fundamentally change the way of work.

What concrete solution did you develop?

Fedor: Helga stores all information about every song and collects all rights associated with the music by processing millions of data sets. Thanks to fully automated end-to-end reconciliation Helga monitors, controls, and detects inconsistencies in revenue streams. Our tool delivers significant information and recommendations in a completely new and augmented way, enabling music professionals to be more data-driven in their decisions, efficient, and paid what is owed.