AI Computer Vision
3DiVi Inc., founded in 2011, is one of the leading developers of AI and machine learning (ML) technologies for computer vision.

3DiVi Biometric
Anti-fraud (BAF)

Technology stack for online identity verification with NIST FRVT top-ranked facial biometrics, advanced liveness detection and user session data monitoring for authentication and identity fraud prevention
3DiVi BAF enables organizations to deliver secure, effortless cross-platform
(iOS, Android, WEB) remote customer onboarding
Streamline a swift and dependable user registration and authorization process with anti-fraud checks using 3DiVi BAF. It's built upon 3DiVi's NIST FRVT-validated software components: Liveness, Verification, and Matching. To further bolster the reliability of checks, session analysis is employed. This involves analyzing data from the user's environment to generate risk alerts.


Zero trust: each user session has unique parameters that cannot be reused by fraudsters to fake
Unique facial recognition: recognition algorithm based on image quality, source, designed specifically for the remote identification, top NIST rankings
Comprehensive liveness check: highly reliable protection against malicious actions using printed face images, masks, video playback, based on several algorithms
Easy embedding in browsers and apps: SDK for Web, Android and iOS
Optimized algorithms perform checks and comparisons in seconds
Scalability: configurable load variation depending on scenarios used and performance requirements
Quick start: simple API for integration into the other information systems
On-premise: 100% data-sovereign, customer-run software, no user data sent to 3DiVi
Quality of the facial recognition algorithm (biometric template extraction and comparison)
Quality of Liveness algorithm according to APCER - Attack Presentation Classification Error Rate(proportion of images containing an attack that were erroneously classified as real face images)
Quality of Liveness algorithm according to BPCER - Bona Fide Presentation Classification Error Rate (proportion of real face images that were erroneously classified as images containing an attack)

Try 3DiVi BAF Now

Ask an Expert
3DiVi computer vision experts are always ready to help you to find a solution matching your requirements