Label Cleanup is a web-based metadata cleaning tool designed to help users inspect and remove supported AI-related source tags, Content Credentials, and personal metadata embedded in photos and videos before sharing them online. Users can upload a final media file and run a free scan to identify information attached to it, including AI source declarations and readable privacy data such as GPS coordinates, capture dates, device information, and creator details.
The platform supports common image and video formats, including JPEG, PNG, WebP, TIFF/DNG, MP4, and MOV, with files up to 200 MB. Its cleanup process handles supported C2PA Content Credentials, XMP, EXIF, and IPTC metadata while preserving the underlying photo or video data. After cleaning, the platform scans the output again so users can review and download the checked copy.
Label Cleanup is particularly designed for content being prepared for platforms such as Instagram, Facebook, TikTok, X, LinkedIn, and Pinterest. Importantly, it focuses on metadata cleanup rather than visual editing: it does not erase visible logos or text watermarks, alter image pixels, or remove pixel-based invisible watermarks. The free service covers scanning and viewing findings, while actual metadata cleaning requires a subscription.