Loti applies facial-recognition AI to content-protection workflows for individual creators. The differentiator from traditional DMCA services is the matching technology — instead of relying on filename-and-fingerprint-based search, Loti can find unauthorized uploads of your specific likeness across platforms. The use case is highest-value for performers and creators whose face appears in their content (the matching does not work as well on content where the face is not visible).
How facial-match enforcement works. Loti maintains an internal model trained on the creator's reference images and continuously crawls target platforms for face matches. When a match is detected, the service issues a takedown notice citing the creator's ownership. The creator does not have to manually identify each infringement — the platform does the detection.
Privacy considerations. The creator has to provide reference images of themselves to enable matching; the service holds and processes biometric data accordingly. Read the privacy policy carefully and understand what happens to your facial data if you cancel.
Limitations. Does not protect content where the face is obscured, masked, or framed out. Does not work as well on heavily-edited or filtered content. Effectiveness depends on the platform's response to DMCA notices — the AI finds the infringement faster, but the takedown still depends on the platform complying.
Bottom line. Useful tool for performers and creators where face-match-based enforcement actually works. Combine with traditional DMCA services for content where face-match does not apply. See DMCA Force for the broader takedown-service category.