Biography
TagTeam Analysis has created a highly intuitive music tagging platform that combines ML capability with human analysis to create highly accurate descriptive music tags for music discovery and search engine optimization.
Q. What is your business model and how do you plan to monetize?
A. We provide music library services to the production music industry in the form of data clean ups and organization, music tagging and TuneTagger subscriptions. We have been in business since 2011 and are currently monetizing from our services.
Q. Why did you choose to start this business in this industry?
There was a need for descriptive music metadata in the production music industry. TagTeam was created in 2011 to help many boutique libraries as well as large music libraries i.e. Shutterstock and Epidemic Sound to achieve strategic and accurate metadata practices as well as provide taxonomy creation based on the specific needs of each library. We have developed tagging strategies that combine human analysis with automation and currently working on ML with our over 200k database of fully tagged tracks of all genres and styles. We believe AI enhanced with quality human-based data outperforms search powered by AI alone.
Q. What qualifications do you and your management team have?
A. I have over 15 years working with production music libraries. My previous employment at Pandora Media and working with the Music Genome Project has helped me master a deep understanding of descriptive music analysis. Sylvia Riege, Developer and Data Scientist, has worked as TagTeam’s Lead UI Developer and Data QA Specialist since 2013. Graduating Cum Laude from UC Berkeley with degrees in Music and Cognitive Science, Sylvia’s background includes: custom Excel-native interface design for music libraries, workflow optimization, custom UI design and systems architecture, database management and QC for small, medium and large-scale datasets as well as ML skills and development skills in React.