Music captured incidentally in live events, venue footage, sports clips, and social content routinely triggers copyright claims, muted audio, and distribution blocks. AudioShake's system identifies the music present — including song identity and rights holder metadata — and removes it before or during distribution, allowing teams to publish or redistribute content without infringing on music rights they don't hold. This supports DMCA compliance workflows for broadcasters, sports leagues, and creator platforms at scale.

Yes. AudioShake's separation model isolates music as a discrete audio element, leaving dialogue, crowd noise, commentary, and ambient sound intact in the output. This makes it well-suited for live sports broadcasts, events, and streaming workflows where crowd atmosphere and commentary are part of the content's value.

AudioShake's music detection model scans audio or video content, identifies where music is present, and returns song-level metadata including track title, artist, and rights holder information. The music removal model then separates and eliminates the detected music from the audio, producing a clean output with all other elements — dialogue, ambient sound, and effects — fully preserved. The two models work together as AudioShake's Copyright Compliance system and are available via SDK for real-time and on-device workflows.

Yes. AudioShake supports video input formats including MP4 and MOV. Music is separated from the audio track and the clean output is returned alongside the original video file structure. This is the most common application for UGC platforms, broadcasters, and content distributors who receive video content with embedded music that needs to be cleared before publishing or monetisation.

AI separation identifies music as a distinct audio source and removes it cleanly, preserving dialogue and effects intact. EQ filtering and phase cancellation remove frequency ranges, which damages speech quality and leaves audible artifacts in the remaining audio. AudioShake's models are trained to understand audio by source type, producing a clean music stem and a clean dialogue stem rather than a degraded mix with reduced music presence.

No. AudioShake works directly from fully mixed recordings — no original stems, multitrack sessions, or source files are required. This is particularly important for compliance workflows where content is often archival material, licensed footage, or third-party productions delivered without session data.

Enterprise teams integrate AudioShake's Commercial Music Removal model into their content management or distribution pipelines via API, enabling automated detection and removal before content reaches distribution. Processing is triggered programmatically and returns clean output without manual intervention per file. This applies in post-production studios, broadcast networks, and content platforms handling archival footage, live recordings, and third-party produced material.

Any fully mixed recording containing commercially licensed music, background tracks, licensed themes, and incidental music can trigger copyright claims, platform takedowns, or licensing disputes at the point of distribution. The risk surfaces when content is uploaded or distributed on platforms using audio fingerprinting. For enterprise teams managing high volumes across multiple platforms and territories, the exposure compounds quickly, especially for archival content where original licensing agreements may no longer cover current distribution channels.