Privacy First
Authentication designed to secure billions of humans, not just devices.
Very AI unites next-gen palmprint biometrics with AI-powered deepfake detection to enable effortless, hardware-free authentication.
With 28M+ scans and over a decade of R&D, Very AI delivers unmatched accuracy and protection in the age of generative fraud.
001
Innovation Gap
Generative AI is fueling new fraud—deepfakes, cloned voices, forged documents—that traditional biometrics and KYC can’t stop. Very AI combines palmprint authentication with proprietary deepfake and AI-detection technology, creating a layered defense that blocks both spoofing and the growing wave of AI-generated attacks.
002
AI and Deepfake Threat
Generative AI enables synthetic identities, cloned voices, deepfakes, and forged documents that evade traditional biometrics. Very AI counters these threats with proprietary classifiers for deepfake video, detectors for synthetic images and audio, and forgery checks for documents—layered alongside palmprint authentication to resist biometric spoofing and AI-driven fraud.
003
Palm Scan: How It Works
Capture → Palm scanned by any smartphone camera
Process → Local feature extraction + encryption
Verify → Identity + liveness confirmed in real time
Output → Instant match/no-match decision
004
System
FAR
FRR
Hardware Required
Notes
Very AI
1 × 10⁻⁷
1.5 × 10⁻²
None (any camera)
Software-only, 10x stronger
Apple Face ID
~1 × 10⁻⁶
n / a
Infrared depth camera
Hardware-dependent, spoofable
Very AI outperforms Apple Face ID by a factor of 10× while requiring no hardware beyond a standard camera.
005
Scaling to a
Global Population (~8.1B)
To guarantee uniqueness at a global scale, FAR must be lower than 1/8.1B (~1.2 × 10 ).
-10
5
Scans per palm
Dual-Palm
Enrollment (left + right palms)
2.5×10
-14
FAR
1 × 10
-9
FRR
006
Very AI vs. Other Biometrics
Unlike fingerprints that degrade and faces spoofed by deepfakes—or iris and DNA scans that are accurate but costly—palmprints are distinct even among twins and never left behind. Very AI turns this advantage into a software-only, globally scalable solution that’s 10× more accurate than face or iris recognition.
