Cyanite provides AI-driven solutions for automated music tagging and advanced search functionality designed for music professionals and organizations. The platform analyzes audio content using proprietary computer vision algorithms that convert music files into spectrograms and identify patterns through learned recognition systems. The technology delivers comprehensive metadata including genre classification, mood detection, instrument identification, lyric themes, and tempo analysis across entire music catalogs.
The platform offers three core access methods for different user needs. The web application provides direct music analysis and catalog management capabilities for individual users and teams. The API integration enables developers to embed tagging and search functionality into existing music systems and workflows. Content management system integrations connect with major platforms including SourceAudio, Synchtank, Reprtoir, and others for seamless catalog operations.
Auto-tagging functionality processes thousands of tracks within minutes, generating rich metadata sets with industry-standard taxonomies covering 26 distinct categories. The system analyzes complete audio files from beginning to end to capture every musical element, mood shift, and instrumental detail. Natural language descriptions accompany tags to provide contextual summaries of song characteristics and emotional qualities suitable for licensing and playlist curation.
Search capabilities include similarity matching that identifies tracks by sonic characteristics, musical vibe, and era with filtering options for genre and tempo. Free text search converts user prompts into musical matches whether queries are brief descriptions or detailed specifications. Advanced search combines multiple parameters and filters to locate specific musical elements within large catalogs.
The platform processes only audio content without relying on embedded metadata or external language models. All algorithms are developed in-house ensuring data security and GDPR compliance with EU-based server infrastructure. Over 35 million songs have been tagged through the platform with continued daily growth across music libraries, publishers, distributors, audio branding agencies, and radio operations worldwide.
- Automated tagging of large music libraries with genre, mood, instrument, and tempo metadata
- Similarity-based track discovery matching sonic characteristics and musical era across catalogs
- Free text search converting natural language descriptions into precise song recommendations
- Music licensing workflow acceleration with AI-generated descriptions and contextual summaries
- Playlist curation powered by comprehensive mood and genre classification systems
- Catalog standardization across acquired music libraries and sub-publishing deals
- Integration with content management systems for unified metadata across platforms
- Audio branding project searches using detailed musical attribute filtering
- Radio and retail music selection based on specific atmospheric and tempo requirements
- Distribution catalog enrichment with consistent tagging for improved discoverability
- Music technology platform enhancement through API-based tagging and search capabilities
- Sync placement preparation with detailed track metadata and natural language descriptions

