AudioMuse-AI transforms your self-hosted music collection into an intelligent sonic discovery universe that generates groove-aware playlists without relying on tag metadata or external streaming APIs. The platform scans audio files directly to extract acoustic properties, rhythmic cadence, harmonic density, and lyrical themes across seventy-two supported languages. Listeners can explore their library through a dynamic two-dimensional interactive music map, discover hidden sonic connections between distant genres, or chart smooth transitional song paths between two completely different tracks. Custom prompt-based querying lets users request niche vibes like late-night lo-fi piano, while automated clustering groups acoustically similar tracks into fresh, genre-defying collections. With Song Alchemy, curators fine-tune playlist moods by interactively adding or subtracting acoustic traits before exporting clean tracklists back to Navidrome, Jellyfin, LMS, Lyrion, Emby, or Plex. A built-in acoustic fingerprinting engine even identifies mystery tracks from twenty-second audio snippets, deduplicating songs across multi-server topologies so every file is processed only once. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.