Automatic music tagging
Analyze tracks for genre, mood, instruments, lyric themes, tempo, and other attributes. These tags give incoming releases and older repertoire a consistent metadata structure.
AI music tagging and catalog search for publishers, libraries, and music platforms.
Cyanite is an AI music analysis and discovery platform for teams that manage music catalogs. It turns tracks into searchable metadata and written descriptions, helping teams organize repertoire and find music for creative briefs, licensing, and recommendations.
Teams can work directly in its web app or integrate analysis and search into their own systems through an API. Its core workflow combines automated catalog tagging with searches based on reference tracks or natural-language prompts.
Analyze tracks for genre, mood, instruments, lyric themes, tempo, and other attributes. These tags give incoming releases and older repertoire a consistent metadata structure.
Generate written descriptions that capture a song’s character and mood, adding readable context alongside structured tags.
Find tracks by sound, vibe, and era, using songs from your library or external Spotify and YouTube references. Narrow results with filters such as genre and BPM.
Search a catalog with short prompts or detailed creative descriptions, translating musical requirements into track matches.
Use multiple tracks as search references to support playlist creation and music recommendations.
Map songs to brand attributes and use mood and genre analysis to support music selection for branding projects.
Music publishers and licensing teams can use a client’s reference song or creative brief to find suitable catalog alternatives, including tracks beyond a curator’s familiar selections.
Music libraries and sync marketplaces can integrate search into their customer experience and generate metadata and descriptions as tracks enter the catalog.
Agencies can support proposed track choices with musical attributes tied to a brand, giving clients a clearer rationale for creative decisions.
Labels and distributors can automate initial metadata preparation for new uploads and large archives, reducing the manual work needed before music becomes discoverable.
Radio and retail music teams can use mood-aware and genre-aware analysis to build playlists and apply consistent tagging across new and existing repertoire.
The web app supports catalog uploads and search without coding. Integrating Cyanite’s analysis and search into an existing platform through its API requires coding skills.
Publishers can sync tagged catalogs to DISCO or their own platform. The API also allows music companies and software teams to incorporate analysis and discovery into their existing systems.
It can support a workflow with human review. In Cyanite’s Marmoset case study, the team remains involved in tagging while using automated analysis as a starting point and a consistency aid.
Cyanite states that it uses EU-based servers and is GDPR compliant. It also says its algorithms are developed in-house without reliance on ChatGPT.
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