Cyberette provides AI-native deepfake detection for identity, fraud prevention, and investigations. The technology detects AI-generated and manipulated image, video, and audio, enabling real-time protection in identity workflows and deeper analysis when evidence is required.
For identity and fraud teams, deepfakes can be detected during account creation, biometric authentication, and account recovery, helping prevent AI-driven impersonation before access is granted or fraud occurs.
For investigations, multi-layer analysis goes beyond a detection score to show where suspicious signals appear and what evidence supports the result. Explainable findings can include relevant regions, timestamps, metadata, and provenance signals, giving teams a clearer basis for further action.
Use cases span financial services, law enforcement, defence and intelligence, trust and safety, legal investigations, child safety, and digital risk. Available as a WebApp or API for direct use or integration into existing workflows.
Cyberette started with a problem that became personal. A friend of the team had their identity used in deepfake content as part of a romance scam. It showed us how quickly AI-generated deception was moving from something experimental into something that could cause real financial and personal harm. At the same time, we saw a wider gap in how organisations were responding. Identity systems needed to detect AI-driven impersonation before fraud happened, while investigators needed more than a simple “real or fake” score after an incident. They needed to understand what had been manipulated and why it had been flagged. That shaped what we built to a technology that can detect AI-generated deception early enough to help prevent fraud, while providing explainable evidence when deeper investigation is needed.