SONOTELLER is an AI-driven audio analysis tool designed to extract detailed metadata from music tracks. By uploading an audio file, users receive an automated breakdown of musical characteristics including genre classification, mood descriptors, instrumentation, BPM, key, and scale. The platform also generates text descriptions and tags suitable for use in music licensing, playlist curation, and content organization workflows. SONOTELLER targets music professionals, content creators, and businesses that need to catalog or describe large volumes of audio content efficiently. The service appears to operate via a web-based interface, allowing users to analyze tracks without requiring specialized technical knowledge. Its outputs are structured to be actionable for downstream tasks such as metadata tagging, sync licensing submissions, and music discovery applications.
Target audience and deployment
- Solo / Freelancer
- Startup
- SMB
- Cloud
Key features
Use cases
- Analyze music tracks for metadata tagging
- Generate descriptive text for music licensing
- Curate playlists by mood and genre
- Catalog large audio libraries efficiently
- Support music discovery applications
Best for
- Music supervisors who need to quickly tag and describe tracks for sync licensing submissions
- Independent musicians who need to generate metadata and descriptions for their releases
- Playlist curators who need to organize tracks by mood, genre, and tempo at scale
- Music library managers who need to catalog large volumes of audio content efficiently