OnID Biometric Facial Recognition is a biometric identity verification system that identifies or authenticates individuals by analyzing unique facial features using AI and deep learning algorithms. The system maps facial landmarks — such as eye distance, cheekbone shape, and jawline contours — and converts them into encrypted digital templates used for either face verification (1:1 comparison) or face identification (1:many database search). Key capabilities include: - Real-time facial data processing via cameras or dedicated biometric scanners - Liveness detection to prevent spoofing via photos or videos - Adaptability to varying lighting conditions, angles, facial expressions, and partial obstructions (e.g., glasses, masks) - Support for on-premises or cloud-based deployment - Multi-modal biometric support, allowing facial recognition to be combined with fingerprints, palm veins, or voice patterns The system targets use cases across corporate access control, financial services (customer onboarding, fraud prevention), healthcare (patient/staff verification), government (border control, surveillance), and retail/hospitality (personalized experiences, secure payments). Biometric templates are stored as encrypted mathematical representations; actual facial images are not retained. The system is stated to comply with GDPR and CCPA data protection regulations. The product supports integration into mobile apps, desktop systems, cloud platforms, and on-premise infrastructure.