Quincy organises chaos of music discovery

As the volume of music uploaded daily continues to grow, efficient catalogue management has become a major challenge for the industry. Quincy, a music classification platform developed by Triple S Solutions and Gold Tea Productions, applies automated analysis to address issues in metadata accuracy and discovery.

With around 100,000 new tracks added to streaming platforms every day, incomplete or inconsistent tagging has contributed to an estimated $2.5-billion in unclaimed royalties. Quincy is designed to process thousands of tracks within minutes, reporting up to 80% accuracy in genre classification, mood analysis, lyrical content, and thematic tagging.

The system aims to improve identification of hybrid and niche genres and includes mood detection to support music selection for a range of contexts. It also offers thematic search capabilities, enabling users to discover songs based on conceptual meaning rather than keywords.

Quincy supports multilingual tagging, making songs in any language searchable and increasing the visibility of music from a wide range of regions and styles. Tracks in languages such as Japanese and Zulu are tagged and indexed alongside English-language songs, supporting equal discoverability across the platform.

“I was drowning in our vast music catalogue,” says Dan Joffe, lead publisher for Gold Tea Productions, which operates in South Africa and the USA. “Managing thousands of songs from global artists required something radical.

“Partnering with Steven Cohen at Triple S Solutions, we created Quincy to do the impossible, especially for underrepresented genres like African music that deserve global attention.”

Manual tagging of music catalogues is time-consuming, often requiring editorial teams to spend weeks labelling large volumes of tracks. Quincy automates this process, reducing the workload to a matter of hours. The system enables detailed search queries, such as “upbeat Afrosoul track about love in Zulu,” and returns relevant results with high specificity.

Familiarity bias remains a common issue in music selection, as supervisors are limited to what they know. Quincy is designed to operate without such bias, generating results based on metadata relevance rather than recognition or popularity.

An estimated 87% of tracks on streaming platforms receive fewer than 1,000 plays annually. By improving the accuracy and accessibility of search and classification, Quincy increases the visibility of lesser-known music and supports broader licensing opportunities for artists and rights holders.

Quincy is designed to benefit multiple stakeholders across the music ecosystem:

• Music supervisors gain faster access to relevant tracks, with improved efficiency in the discovery and selection process.
• Record labels and rights holders can ensure their catalogues are comprehensively tagged and prepared for licensing and distribution.
• Artists and creators benefit from increased visibility, as more accurate classification enhances the likelihood of their work being discovered and used.
• Listeners and audiences are exposed to a wider range of curated content, as lesser-known tracks become more accessible for inclusion in media and playlists.

Quincy is designed to improve timing and precision in music catalogue management by addressing common issues such as inconsistent metadata and limited representation of niche or underrepresented genres.

The platform aims to provide equal classification and searchability for all tracks, regardless of language, style, or origin. By enhancing the organisation of music catalogues, Quincy supports more effective discovery and use of a broader range of content.