Show HN: I built an AI music tagger for DJs, fusing metadata, audio DSP, and ML (choon.app)

A new AI tool, Choon, has been launched to revolutionize how DJs manage their music libraries by offering an automated tagging system that categorizes tracks by genre, region, era, and vibe. This solution syncs directly with Rekordbox, allowing DJs to filter their massive collections instantly during sets, making it easier to find the perfect track without the hassle of manually scrolling through thousands of songs. Choon promises to tag large libraries—up to 10,000 tracks in under an hour—all while ensuring that no audio files leave the user's Mac, prioritizing privacy. The significance of Choon lies in its ability to enhance the creative flow of DJs, allowing them to focus on their performance rather than library management. By providing over 50 detailed sub-genres and maintaining the integrity of existing metadata, the tool enables a personalized and efficient experience. Choon's innovative use of AI for metadata analysis not only streamlines the music selection process but also adapts to DJs' unique styles and preferences, thus reshaping how DJs interact with their music collections during live performances.