Cyberette detects AI-generated deceptive images, video, and audio, then shows the forensic evidence behind every result. Investigation, identity, government, and risk teams can understand what was flagged, why it matters, and what to do next.
Backed by:
Human accuracy at identifying deepfakes averages around 55%, barely better than chance. Replace that guess with structured indicators.
was lost to deepfake fraud only in the first half of 2025. (ZeroThreat, 2026)
losses tied to AI-related complaints. (FBI, IC3 2025)
of fraud experts have encountered synthetic identity fraud. (Statista, 2024)
Explore Cyberette's solutions for identifying manipulated content, examining evidence, and preventing fraud across your existing workflows.
Examines digital media across multiple forensic layers, revealing indicators of deception. Each analysis provides actionable findings to help teams understand where to investigate further.
Examine facial movements, expressions, lip synchronisation, and behavioural inconsistencies to identify signs of manipulation.
Pinpoint suspicious regions in images and relevant timestamps in videos and audio with visual indicators.
Inspect available file metadata, content history, and provenance signals to identify inconsistencies.
