MusicAtlas is built to make music searchable and understandable across large collections of recorded music. Features are organized around the same core layers that power the platform: a multi-model analysis pipeline, a multi-representation search index, and the products and APIs that deliver results across workflows and listening destinations.
Reference-track search. Start with any song and find similar tracks by sound, meaning, and context — without relying on manual tags.
Intent-driven discovery. Search by mood, use case, vibe, instrumentation, era, lyrical themes, or creative direction using natural-language prompts.
Open discovery outputs. Results are designed to be reused across platforms and workflows rather than locked inside a single ecosystem.
MusicAtlas Explore Map.
Sonic similarity matching. Find “sounds like” tracks using audio-derived representations that capture timbre, rhythm, energy, and structure.
Context-aware similarity. Similarity is not treated as a single score; multiple representations help distinguish surface-level resemblance from deeper creative adjacency.
Built for commercially released music. Optimized for broad, gap-free search across the recorded music landscape — not limited to stock or library-only catalogs.
Similar Artists Grid.
Fast lyric search. Search for phrases, themes, and concepts across music collections to support discovery, clearance, and editorial workflows.
Theme and meaning exploration. Connect tracks by lyrical intent and narrative arcs, not just exact phrase matches.
Cross-signal discovery. Combine lyric understanding with audio similarity and contextual signals to surface musically and thematically aligned results.
SyncSearch Lyric.
Multi-model representations. Audio, lyrics, and contextual signals are modeled together so search is not constrained to a single tagging or classification system.
Relationship-aware relevance. The platform models how tracks relate across a broad corpus to improve relevance, discovery, and reuse over time.
Works alongside systems of record. MusicAtlas is designed as an intelligence layer that complements existing catalog and rights systems rather than replacing them.
Robin Contexts.
Explore Maps. An open discovery experience designed to help listeners break out of closed algorithm loops and explore music intentionally.
SyncSearch. Search tools for rights owners and partners to discover tracks by sound, lyrics, mood, and use case.
Robin. A discovery workspace for music supervisors and editors, built for fast exploration and non-obvious matching.
MusicAtlas GPT. A conversational interface for exploring music intelligence using natural language, powered directly by the MusicAtlas search and similarity engine.
SyncRep Artist Memberships. Artist-facing tools that apply the same intelligence layer to help creators understand positioning, similarity, and discovery context for their own releases.
Track-level intelligence API. Build search, similarity, enrichment, and discovery workflows using MusicAtlas as the intelligence layer.
Designed for integration. Lightweight APIs make it easy to connect MusicAtlas to existing tools, portals, dashboards, and internal workflows.
Cross-platform outputs. Results can be routed into downstream tools and listening destinations rather than optimized for a single platform.
POST /similar_tracks
{
"artist": "The Beatles",
"track": "Hey Jude"
}
→ Returns: Top 20 matches
POST /describe_track
{
"artist": "Radiohead",
"track": "Kid A"
}
→ Returns: Sonic + characterstic data
Fast, high-confidence “sounds like” matching across large music collections.
Lyric-driven discovery for themes, narratives, and clearance workflows.
Cross-platform playlist building and editorial exploration.
Music intelligence that improves relevance and discovery over time.
Developer-ready building blocks for new products powered by music search.