A.V. Mapping is a video-music matching and licensing platform: deep learning models analyze uploaded video content – mood, pacing, emotional arcs, scene detection, characters, shot rhythm, and color tone – to recommend music that fits emotionally, not just by genre tag. Video-to-music, image-to-music, and text-to-music modes let a creator start from whichever asset they already have, and users can also search directly by emotion, tempo, genre, or instrument.
The real-musician sourcing is the detail that matters most for anyone licensing music professionally: A.V. Mapping matches video to tracks performed by real musicians rather than synthetic AI-generated music, which keeps the output usable for licensing contexts (film, broadcast, advertising) where AI-generated audio carries unresolved rights and provenance questions. The platform states it compresses a typical six-month music licensing cycle down to roughly eight seconds of matching time.
A.V. Mapping offers a developer API (1,000 calls/day on the standard tier, enterprise tiers with higher limits), instant licensing, and post-production tools like noise reduction and sound effects, with a creator-first licensing model returning 70% of public performance royalties to music creators. Software plans include a 14-day free trial with no credit card required; music licensing pricing varies by location, usage, and purpose per a published reference price list.
