Enterprise-Grade Liveness Detection Capabilities
Every capability built for identity verification teams who need passive, frictionless presentation attack detection
Passive Detection Capabilities
Physiological signals that verify human presence without user cooperation
rPPG Blood Flow Analysis
Detects the involuntary micro-color changes caused by cardiac blood flow in facial tissue, producing a physiological signature unique to living humans
Temporal Signal Verification
Analyzes the time-domain characteristics of physiological signals across multiple facial regions to confirm biological consistency
Multi-Spectral Spoofing Detection
Cross-references color channel responses to identify the optical properties of screens, printed media, and synthetic materials
Deepfake Video Detection
AI-generated videos lack authentic rPPG signals. Circadify identifies the absence of genuine physiological patterns that deepfake generators cannot reproduce
Passive Detection Capabilities
Integration and Deployment
Built for identity platform teams who need reliable, scalable liveness infrastructure
Standard Camera Compatibility
Works with any RGB camera, including smartphone front cameras, laptop webcams, and kiosk sensors. No infrared or depth hardware required
Edge and Cloud Processing
Run liveness detection on-device for data sovereignty requirements, or via cloud API for rapid deployment. Both paths deliver the same detection capability
API-First Architecture
RESTful API with SDKs for iOS, Android, and web. Integrates into existing identity verification flows with minimal engineering effort
Integration and Deployment
Passive Liveness vs Active Liveness
| Feature | UseFaceScan | Traditional Methods |
|---|---|---|
| No User Interaction Required | ||
| Zero Onboarding Friction | ||
| Defeats Deepfake Video Attacks | N/A | |
| Physiological Signal Verification | Varies | |
| Standard Camera Only | Limited |
Experience UseFaceScan Today
See what contactless vitals monitoring can do — try it free.