Liveness Detection
Anti-spoofing that tells a real, present person from a photo, video replay or mask in milliseconds.
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Alfabeta Liveness Detection protects face-based systems from presentation attacks by confirming that a genuine, living person is in front of the camera. It analyses subtle cues such as texture, depth, micro-movement and reflection to distinguish real faces from printed photos, screen replays, cut-outs and 3D masks.
Available in both passive and active modes, it adds a critical trust layer to authentication and onboarding without slowing users down. The engine runs on standard RGB cameras, requires no special hardware, and integrates with face recognition and e-KYC flows through simple APIs.
Presentation Attack Defence
Blocks photo, video replay, cut-out and mask spoofing before a face is accepted as genuine.
Passive And Active Modes
Choose silent, single-frame checks for speed or challenge-response actions for higher assurance.
No Special Hardware
Works with ordinary RGB cameras on phones, kiosks and access terminals โ no depth sensor required.
Millisecond Decisions
Returns a real-or-fake verdict in a fraction of a second to keep authentication frictionless.
Pairs With Face Recognition
Gates every identity match so only live, present users are ever verified or enrolled.
Simple API Integration
Drop liveness into web, mobile and kiosk apps through clean, well-documented endpoints.