AISWare AN Evo

AsiaInfo's AN EVO is an advanced Autonomous Network product based on large model and AI technologies, provides CoPilot and Agent toolkit for AN scenarios.

Unique Advantages

Core Values

01

Improve Efficiency

  • Faster access to real-time network data
02

Reduce Resolution Time

  • Improve in the troubleshooting efficiency by quickly locating and solving problems.
03

Reduce OPEX

  • Reduce over 1M USD annual cost by using AN Evo.

Application Scenarios

Network Operations Management
  • Multi-Round Natural Language Queries
  • Network real-time data analysis
  • Intelligent decision making for business analysis
Smart Deployment and Maintenance
  • Large Model Reasoning Planning
  • Problem Intent Understanding
  • Plan Formulation and Scheduling
Network Smart O&M
  • Intelligent network fault monitoring
  • Automatic fault cause localization
  • One-click Disposal Suggestion
  • Fast repair of network faults
Network Service Provisioning
  • Business Requirements Collection Management
  • Intelligent design of business solutions
  • Orchestration process fault self-healing
Perception Analysis
  • Automatic identification of potential complaints
  • Intelligent positioning of complaint problems
  • Intelligent recommendation of repair strategies
Network Quality Assurance
  • Automatic perception of quality problems
  • Intelligent generation of expert program
  • Intelligent repair of quality problems

Customer Success Stories

Data platform project with LLM

The radio network optimization system integrates AN Evo to achieve guided knowledge Q&A and network problem analysis, assisting engineers to efficiently handle wireless quality complaints, and supporting O&M personnel to analyze and obtain solutions in natural language.

  • over 90% Network Complaints Covered
A regional network smart O&M project

The network fault system integrates AN Evo helps complete fault disposal in a closed loop and enhance the O&M efficiency, through intelligent inspection and monitoring of equipment, automatically finding and analysing faults, generating treatment plan recommendations.

  • 80% Increase in fault handling efficiency

Documents