Data Centre

Mining fused data and exploring data value to achieve 1+1>2

Pain Points


Single data

Single data category, poor correlation, information silos


Data Breach

Use raw data information for calculation, easy to be stolen


Data Transition Acquisition

Transitional data collection, facing the security risk of data transmission and storage


Simple data integration

Simple data integration and no expanded value of the integrated data


Solution Architecture Diagram

Solution deployment/introduction

  1. Privacy computing platform deployments typically include a cryptographic computing platform plus several data source clients, with the Trustkernel providing a platform-based Sass service or an API-based Pass service

  2. Computing platform data calculation volume is limited by hardware bottleneck, 7 billion data volume, expected to deploy 10 hardware servers

  3. With the help of privacy computing, we can use DataCube to open up data nodes and unite multiple data sources to improve the operation capability of customers' digital assets while protecting user information from leakage.

Core Features

High Performance

Using TEE technology to ensure that the operation is not disturbed to speed up the calculation speed

Hardware Level Security

Hardware-based trusted computing technology, more secure and reliable


Supports multiple data fusion and privacy calculations

Application Scenarios


Intelligent risk control in the financial industry


Smart Clinical and Management in Healthcare Industry


Government industry data integration