Four detection layers.
One definitive verdict.

Our neural network analyzes facial geometry, skin texture consistency, blinking patterns, and micro-expression timing to identify AI-generated face overlays — even when they're imperceptible to the human eye.

Trained on millions of synthetic and authentic assets, this module flags objects, backgrounds, and props that exhibit hallmarks of AI generation — unnatural lighting gradients, impossible physics, or artifact bleeding.

Every camera and editing pipeline leaves a unique fingerprint. We detect when that fingerprint has been tampered with — inconsistent compression blocks, re-encoding signatures, and GAN-specific noise patterns.

Authentic human movement follows biomechanical laws. Our model scores the naturalness of motion — from subtle head sways to full-body dynamics — detecting the uncanny valley that AI-generated movement cannot escape.