Simplify your identity verification methods with technology that leverages accurate machine learning algorithms to crop, rectify and recognise ID documents, while detecting facial features for a precise face biometric verification. Our commitment to excellence drives our technology teams to continuously innovate algorithms for document and facial recognition solutions. With our automated identity verification solutions, companies in the insurance, fintech, telco [...] industries can adapt their technology to meet their unique needs and use cases.
Future-oriented Identity Verification Technology
Benefit from Swiss technology that is developed
in-house and designed with a focus on
future-oriented solutions.
Sophisticated Machine Learning Algorithms and advanced Computer Vision for your Business’ Success
Leverage from the technical basis of our solutions, that is a combination of AI applications such as state-of-the-art computer vision for machines, geometric object recognition, as well as machine learning methods.
Gain an extensive independence from third-party vendors. Our high security standards, and constantly evolving technology ensure that identity verification solution technologies are always up-to-date, helping you to precisely convert more customers.
Get the benefit of our extensive internal knowledge about ID documents and other documents i.e. drivers licenses on a global scale. This allows our development and product teams to adjust for customer requirements flexibly and quickly.
Enhance your seamless interconnectivity. Our design enables both us and our customers to tailor our solutions to a wide range of applications. They can be seamlessly integrated into existing workflows in a matter of days.
![Step 4 - Take a selfie (1)](https://www.pxl-vision.com/hs-fs/hubfs/Website%20Development%20Assets/Icons/Step%204%20-%20Take%20a%20selfie%20(1).png?width=150&height=150&name=Step%204%20-%20Take%20a%20selfie%20(1).png)
Just a single selfie taken by the user to determine if a real person is using our solution. This is combined with a machine learning process that verifies that the face on the document matches the user's face, resulting in a high level of accuracy.
Ensure only fraud-proof technologies are integrated into your workflows. Our algorithms are trained to detect invalid or forged documents and to detect fraudulent face alteration activities. Keep track of the fraudster activities and eliminate them from your platforms in a matter of seconds.
![Specimen 1](https://www.pxl-vision.com/hs-fs/hubfs/Specimen%201%20.png?width=1004&height=650&name=Specimen%201%20.png)
We innovate our technology constantly
Ensure highly secure and accurate identity verification procedures with our innovative approaches to field detection and document cropping. Clear images from the start mean fewer errors and higher conversion rates.
Minimise the need for manual correction, improving user experience and compliance across industries, with our automated, precision-focused approaches.
Our Core Technology & Research Areas
With our technology, we seek to increase the accuracy, automation, and reliability in identity verification. We have developed globally unique, patent-pending approaches:
- The recognition, classification and determination of ID document authenticity;
- Facial biometrics, including face verification and zero-interaction passive liveness detection;
- Methods for efficiently dealing and working with sensitive personal data.
Technology that you can trust
Our technology is not only highly efficient, but also compliant - we automatically remove personal and sensitive data from our backend in accordance with our clients' and end users' requirements.
Trust our state-of-the-art technology that underpin our innovative products
Our state-of-the-art machine learning technology allows us to onboard different documents without having to write code. It accurately detects and extracts relevant information even under difficult and changing conditions, such as lighting, different device properties, reflections, damaged documents, blurriness and so on.
Document Agnostic Processing
Allows our document experts to configure new and existing documents by defining the locations of relevant information, including features such as text fields, facial images and security
features, using our in-house onboarding tools.
The Optical Character Recognition (OCR)
Advanced Field Detection
After scanning, our field detection algorithms take over, ensuring the precise location of critical data such as names and numbers.
This not only increases the accuracy of the Optical Character Recognition (OCR), but also significantly reduces errors, enabling smoother
and faster KYC processes.
Universal Document Embedding
It is a set of numbers that capture the visual footprint of a document. This allows us to onboard and start recognising new documents with a single sample image.
Recapture Detection
It recaptures detection of documents from screens, as well as consistency checks of Machine Readable Zone (MRZ) and Visual Inspection Zone (VIZ) field contents.
Enhanced Document Cropping
Our technology can skilfully scan documents in the midst of clutter or poor lighting. Imagine your badge lying on a busy desk - our system will find it and capture it.
Academic Partnerships
Our collaboration with leading academic institutions, such as the ETH Computer Vision Lab (CVL), the Berner Fachhochschule Computer Perception program and Michigan State University help us improve and further develop our technology.
We have recently joined forces with Swiss research institute Idiap to combat fraudulent AI-generated facial images and travel documents. The 18-month-long project, funded by the Swiss innovation agency Innosuisse, aims to bring the world's first robust solution for deep facial recognition to market.
![Computer-Vision-Lab Computer-Vision-Lab](https://www.pxl-vision.com/hs-fs/hubfs/Logos%20(Clients%20%2B%20other)/Computer-Vision-Lab.png?width=1920&height=1080&name=Computer-Vision-Lab.png)
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![Idiap logo Idiap logo](https://www.pxl-vision.com/hs-fs/hubfs/Idiap%20logo.png?width=1382&name=Idiap%20logo.png)