AISWare AI² is an infrastructure used to build large-scale intelligent services. It is the hub of the middle-ground of companies, which can provide step-by-step construction of algorithm models and full life cycle management services for the intelligent transformation of companies. It can help companies continue to deepen their own businesses to obtain algorithm models and achieve the purpose of reuse, combination of innovations, and large-scale construction of intelligent services. It can provide strong scenarios, low-cost, integrated software and hardware solutions and standardized AI applications for the intelligent transformation of companies.

Product superiority

Product value


Lowering the barriers for developing AI services

  • Diversified modeling methods create intelligent modeling experience.
  • The threshold of AI development is lowered, so that ordinary AI developers can also achieve the level of 80 points

Reducing the cost of using AI to integrate intelligence

  • Highly integrated operating environment
  • Plug-in deployment
  • Multi-specification calculation engine
  • One-stop development experience

Improving the quality of building AI services

  • Presetting excellent models and typical characteristic data accumulated by various industries
  • High-quality AI services can be quickly built through the stable and efficient AI cloud platform

General AI services and industry models

  • Customers are provided with a solution to directly and quickly call AI capabilities to quickly meet service needs.

Application scenario

One-stop AI capability development
  • Connecting the data flow
  • Linking the production process
  • Integrating AI capabilities
Middle-ground empowerment with AI
  • Full scenario empowerment
  • Whole process empowerment
Contributing to the data mining of customers
  • Diversified model development tools
  • Excellent industry models and data characteristics
  • Intelligence aided modeling
Cloud-edge computing-terminal collaboration/edge empowerment
  • Cloud-based calculation engine
  • Edge AI solution integrating software and hardware
  • Empowering edge business scenarios of various industries

Customer success case

AISWare AI² has built an AI middle-ground for a provincial telecom operator

Due to the problems such as inconsistent data standards, inconsistent service scheduling, inconsistent authority management, failure to link up end-to-end processes, failure to share platform resources, and lack of data protection standards resulted from the past “shaft-style” AI capability building, the provincial operator was in urgent need of constructing a set of one-stop end-to-end digital intelligent middle-ground.On the basis of AsiaInfo’s AISWare AI², an AI data middle-ground has been built to provide full-process AI development capabilities, integrate data middle-ground and technical middle-ground, realize the global empowerment of B/O/M, and provide multiple intelligence integration methods and multiple deployment methods, thus realizing the comprehensive empowerment of different scenarios, and the empowerment for the full process from perception to cognition to decision-making.

  • 900w The daily AI service invocation exceeds on average
  • 50% The workload of AI service development is reduced by
  • 60% Launching cycle of AI capability is reduced by
  • 180% The operation frequency is increased by
AISWare AI² has implemented a centralized machine learning platform for a group customer

In recent years, the group has attached importance to the centralized construction of machine learning capabilities, aiming to reduce the overall construction cost of machine learning capabilities for the company through unified construction. Based on this guidance, the group has built a set of unified centralized machine learning platform with the help of AsiaInfo’s AISWare AI², enabling various provinces or professional companies to enter and use the platform in the form of tenants. Through effective multi-tenant management, model sharing viewing, model sharing use, model sharing recycling are realized to reduce the closure level of model and increase the penetration rate of excellent models.

  • 20 The entry of over provincial-level tenants
  • 1.4w More than of model inferences accumulated
  • 257 model trainings
  • 174 model applications

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