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World Class Technologies

  • Top Enterprise Facial Recognition
  • Certified Passive Liveness Detection
  • Computational Photography
  • Robust ID Validation

Top Enterprise Facial Recognition

Top Enterprise Facial Recognition

Incode is recognized as a leader in enterprise-grade facial  recognition by the US Government (NIST).

 

Incode has developed proprietary edge and server facial  recognition. The technology runs efficiently on the edge on  low-end phones with poor-quality cameras and on server,  while maitaining high accuracy levels.

Highly ranked by

Certified Passive
Liveness Detection

Certified Passive  Liveness Detection

Incode’s LiveBeam hardware-less anti-spoofing  technology is the first and only iBeta
certified  liveness that doesn’t require user interaction,  and 1 out of 2 technologies to have received  the iBeta facial liveness (PAD) certification in general.

Incode’s passive liveness solution uses light-modeling to perform liveness with just one photo frame of a user and with banking level security. This helps differentiate between a real person and a photo or video of that person.

Users don’t need to perform awkward active liveness actions (e.g. blinking, raising eyebrows,  keystroking). The solution works on low-end and  high-end devices both native

and on web and  doesn’t require special hardware.

LIVE

Beam

Robust ID Validation

Robust ID Validation

Incode’s ID validation models leave no margin for fraud.

 

Incode’s ID detection runs key tests on the IDs to  net any kind of identity theft attempts. Fake check,  tamper check, and liveness check are some of the  basic deep learning-base validations that run on  the ID to detect fraud.

 

Incode supports a global database of 6,000+ government-issued IDs in over 190 countries.

 

Incode’s facial recognition technology and encryption systems are designed to be secure and convenient in every platform.

Computational Photography

Edge computational photography is the  science of capturing useful frames from users.

 

100+ computational adjustments are  performed to the photo on device and server  to carefully guide the user to take a functional  photo and perform photographic adjustments  (e.g. brightness, contrast, rotation).

 

These user instructions and automatic  adjustments ensure a smooth customer experience and a better recognition capture.