Operation And Maintenance Optimization Of The World’s Leading Power Company


Our client is the world’s leading energy supply company. The parent company has the world’s largest power transmission capacity and the largest scale of new energy grids. It has invested and operated in 9 countries including China, the Philippines, Brazil, Portugal, Australia, Italy, Greece, Oman, and Chile. The backbone of the energy network.

AI provides intelligent dispatching technology for powerful enterprise distribution network maintenance plans, and takes over the monitoring and dispatching work of manual dispatchers for a large number of repetitive positive-division planned maintenance.


Command fatigue, many phone calls, many monitoring information, and long talk time;
The call centre is congested, and there are dozens of incoming calls in the morning and afternoon peak hours, and they cannot be connected at the same time, resulting in delays in maintenance operations;
The decision-making is complicated, and the network framework, system and faults are complicated, and it is often impossible to make effective disposal decisions.


Our core team using NLP and knowledge graph technology to carry out knowledge graph, so that AI can understand the knowledge of distribution network business;
Intelligent dialogue technology: Develop command multi-round man-machine dialogue function for service distribution network business. Training AI engines such as voice models and NLP to make it possible to understand business reports and issue instructions;
Intelligent decision-making technology: Use deep learning, reinforcement learning, and graph inference computing to build an intelligent business decision-making engine to enable distribution network production and command business.


Release the production command work of manual dispatchers

▲10 Million Yuan

Increased revenue from labour cost savings

> 20 Million Yuan

The peak waiting time is shortened from 20 minutes to 1 minute, which can recover the economic loss of more than 20 million yuan caused by power outages in the area

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