Challenges with Existing Solutions
- Low face match accuracy results in increased manual reviews, false rejection rates, false acceptance rates, & operational costs.
- Authentication consumes significant time to match the selfie with millions of database entries, affecting the user experience.
- AI with low accuracy struggles in diverse conditions, including lighting, angles, facial variations, and when masks or spectacles are present.
- Solution encounters compatibility issues with low-end devices and limited bandwidth conditions, limiting its effectiveness.
What We Offer
- Our models have been trained extensively on diverse facial variations and therefore produces highly accurate results regardless of race, age, and gender.
- Our solution works well even with poor camera quality, low-end devices and excels in handling facial features, such as facial hair and spectacles, even in low-light conditions.
- Authenticate in a blink – our solution verifies a selfie against millions of records in just 0.2 seconds, combining speed and accuracy seamlessly.
Input and Output
Integration Made Easy
100+ API integrations supported across regions and industries via ONE SDK
Integrate in less than a week
Dedicated customer support for smooth integration
Build End-to-end Journeys with HyperVerge ONE
Build end-to-end financial product onboarding journeys with ease
Configure user onboarding workflows and UI/UX without code.
Set automated fallback options to prevent user drop-offs during downtimes
Get analytics on conversion rates and optimize the friction points
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Visit Page >Frequently
asked questions
Does your face authentication solution work in low-light conditions or with poor camera quality?
Can your face authentication solution detect and handle facial hair, spectacles, and other variations?
What is face authentication, and how does it work?