ABIS Multi-Modal Biometric Unified Platform

A cross platform, open and scalable unified identity verification platform and identity recognition platform to realize the safe, convenient, true and accurate verification and recognition of user identity
Taking self-developed underlying fingerprint, face, iris, finger vein and multi-modal algorithm as the core, Eyecool establishes ABIS multi-modal biometric identity verification unified platform to realize safe, convenient, true and accurate verification of user identity. Relying on the Eyecool original underlying algorithm and unified data management, it has core functions such as multi-modal data perception, multidimensional data calculation, intelligent feedback decision-making, data security sharing, etc. It’s applicable to the security risk prevention, intelligent identification analysis and identity verification services of computer network application systems in various fields. 



Data Warehousing

Data Retrieval

Face Captured
5,000,000+ devices integration 2,000,000+ personnel data
registered into database per hour

Hundred million level
database retrieval
Searching of face capture
history is on billion level

Entrance Guard

Data Analysis


Easy to Use
Ten million level
personnel access control
Data analysis
system based on identity
Billion level biometric
identity verification
Interface is easy
to use and develop



The platform adopts a variety of algorithms such as face recognition, iris recognition, fingerprint recognition, finger vein recognition, etc. originally created by Eyecool
Technology,  and  provides biometric verification services of multimodal fusion,  effectively improving the adaptability of biometric technology to different people
and different scenes. The platform supports second level response to hundred million level data, and the recognition rate is above 99%.
The platform adopts efficient and  scalable cloud native architecture to realize flexible combination,  rapid and agile deployment and low-cost maintenance of  various
capability service modules. It supports DevOps continuous delivery capability and provides reliable and flexible large-scale distributed computing capabilities.

Computing resources can be expanded. During the usage, the server can be expanded and micro service nodes can be deployed at any time according to customers
business volume demands.

Load balancing, different business requests, automatic allocation of computing power, to avoid some services blocking while some services idle.


The platform has built-in privacy protection capability, which only stores structurally extracted biometric data, does not store customers'  original biometric pictures,
and encrypts, verifies and controls access to biometric data to ensure the confidentiality, integrity and controllable access of sensitive information. Through data trans-
mission encryption and minimizing authorization, ensure the security of data exchange with third-party business systems.

The system establishes an internal audit mechanism before, during and after the event, and has a complete ability of application logs.


With 20 years practical experience in financial industry and  several cases of 140,000 hours of MTTF (minimum failure free interval). The system design is robust
and will not affect the normal works of other businesses when some businesses   upgrade services, fail or have abnormal data.  The platform ensures the stable works of
the system through perfect backup and recovery strategies, reliable operation management monitoring and rapid fault handling means.

The platform has certain fault-tolerant design,  exception handling and disaster recovery capabilities,  which can effectively deal with host exceptions,  service exceptions, communication exceptions and other situations, ensuring correctness and integrity of platform services.


The platform follows the general technical standards in the industry, provides a reliable guarantee for the portability, interoperability and scalability of products. It supports mainstream operating systems  such as Linux and windows,  and the mainstream database such as  Oracle, DB2, Sybase,  SQL server,  MySQL and other commonly
used databases in the industry,  which can effectively use the existing database resources of customers.  The platform provides the docking ability of big data engine, and
enables data intelligent decision-making through biometric technology.

The platform adopts an open architecture design, and provides a variety of standard interfaces for customers to realize flexible secondary development and business sys-
tem docking. It supports the rapid integration of third-party AI algorithms and facilitates the provision of unified and consistent AI service capabilities.


Based on the in-depth understanding of biometric scenes and reasonable technical architecture design, the service module division logic is reasonable (such as attribute detection, feature extraction, data management, liveness detection, etc.), and the function design is flexible and universal (such as biometric 1:1 comparison, 1:N search recognition, image quality detection, liveness detection, etc.), Users can flexibly configure service modules according to business demands.
The platform is equipped with functional application examples, which is convenient for users to master quickly. At the same time, the service monitoring interface is provid-
ed to facilitate users to monitor the service status in real time.


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