Deepfake Detection

Yes — with the honest caveat that detection is probabilistic, not absolute. Generation tools leave traces: statistical artifacts, blending boundaries, temporal inconsistencies in video, and capture characteristics no physical camera produces. A detector weighs those signals into a tiered likelihood result rather than a guaranteed one, and stays effective only if it retrains as new generators appear. ScamAI returns scores with evidence and lets you set thresholds — decline high-confidence fakes automatically, route ambiguous cases to human review.

Recorded media can be scored after the fact; a live call has to be scored while it happens. Halo runs ScamAI's detection on-device during meetings, continuously checking participant faces and feeds for face swaps and manipulated video, and raising a risk signal the moment something synthetic appears — mid-call, while you can still act. Because analysis happens locally, the meeting never leaves the device to be checked, keeping sensitive calls private while they are protected.

Three broad families. Face swaps graft a target's face onto another person's body — the classic impersonation tool. Full generations create an entirely synthetic person, common in fake profiles and synthetic identities. Replays and injections present pre-recorded or synthetic footage as a live capture, often through virtual-camera software. Each leaves different evidence, so ScamAI scores them with distinct signals across images, recorded video, and live calls — catching the synthetic media itself, however it is delivered.