Based on digital technologies such as data asset management, MPC multi-party security computing, federated learning, blockchain, the privacy computing platform AISWare MPC realizes data availability with invisibility, connects enterprises and industry data islands, helps enterprises build trusted data circulation and transactions, activates the value of data elements, and releases huge dividends and powers brought by data elements.

Product superiority

Product value


Interconnection of heterogeneous platforms

  • Realizing multi-level interconnection of multi-party heterogeneous platforms through standardized interfaces in the industry;
  • Breaking down the barriers of intelligent data circulation between heterogeneous privacy computing platforms;
  • Realizing unified control of data, projects, resources and services of heterogeneous cross-field privacy computing platforms;

Activating data values

  • Revitalizing enterprise data assets, giving full play to the value of digital economics, and conducting compliant and trusted data circulation and transactions.
  • Helping enterprises realize data sharing and opening up, and releasing dividends of data elements

Empowering industry innovation

  • Through cross-field data aggregation, realizing fine management, lean manufacturing, precision marketing, and accurate planning in an industry
  • Through data aggregation and analysis, helping the digital transformation and upgrading in an industry;

Helping enterprises form an industrial ecology

  • Realizing cross-departmental, cross-regional and cross-level government data security aggregation,
  • Realizing cross-field circulation of multi-industry data and helping enterprises conduct data ecological construction.

Application scenario

Anonymous query
  • Blacklist query
  • Financial joint risk control
  • Key person retrieval
  • Intelligent credit risk control
Safe intercourse
  • Intelligent insurance risk control
  • Online digital marketing
  • Credit for small and micro enterprises
  • Retention of lost users
Joint statistics
  • Public safety situation
  • Analysis of population mobility
  • Real-time screen of administrative services
Joint modeling
  • Activating silent users
  • Telecom anti-fraud
  • Accurate medical recommendation
  • Accurate automobile marketing

Customer success case

AISWare MPC builds privacy computing platform for an operator's group

To meet the strategic requirements of operators' big data conducting external empowerment and the regulatory requirements of national data security protection laws and regulations, AsiaInfo built a privacy computing platform for an operator group company that adopted centralized construction and provincial operation mode. This project has completed the introduction of federated learning, multi-party security computing, and other technologies, built basic data security integration, query, computing, and modeling capabilities, formed an enterprise-level security capability platform, and formulated a multi-party security computing technical scheme for service operators. The construction of the operator's privacy computing platform can significantly enhance the application value of the operator's massive data and bring new value to the operator's revenue based on the operator's big data advantages.

  • 80% A bank's accurate customer acquisition increased by
AISWare MPC is a privacy computing platform for an operator's provincial company

The operator possesses many users' attribute and behavior data, such as online logs, APP records, and call records. However, the data cannot be empowered for external business due to data partition. Based on the encapsulation of the underlying technology for the multi-party security computing system, a mobile privacy computing platform combines the federated framework and AI algorithm to create an efficient and secure system architecture, interacting with the centralized big data service management and control system to obtain data assets, encapsulate the model and register and convey the computing results, supporting several data service scenarios such as administrative service, medical care, finance, retail.

  • 300% The accuracy rate of a car company's stock replacement model has increased by

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