On August 10, Hua Xiang, the district manager of the Shizhong Power Supply Service Center of State Grid Suzhou Power Supply Company, received a work order from a customer regarding unusually high summer electricity bills. He entered the work order information through the "Su Dian Zhi Ban" (Suzhou Power Smart Companion) platform, and within five minutes, a clear "preliminary handling guidance report" was generated, outlining the verification items, policy clauses, communication scripts, and key risk points, providing precise guidance for frontline work order handling. This highly efficient tool empowering frontline staff is a service work order handling AI system built by State Grid Suzhou Power Supply Company based on the smart platform.

Previously, grassroots power supply teams relied heavily on manual processes to handle a large amount of repetitive work when processing customer request work orders. To reconstruct the full picture of the incident and improve service quality, staff had to manually review various materials, systematically analyze the events, and draft investigation reports, repeatedly refining the content and standardizing document formats. Writing a single report typically took 2 to 3 hours, not only consuming a significant amount of time and energy at the grassroots level but also easily leading to inaccurate problem identification and insufficient risk assessment.

A smart agent for handling service work orders has been developed. Focusing on frontline operational scenarios, this agent possesses four core capabilities: initial service incident handling, investigation report writing, work order analysis and quality review, and investigation report format optimization. It can generate three core documents with a single click: an initial handling guidance report, a closed-loop work order analysis report, and a work order quality review report. The State Grid Suzhou Power Supply Company has simultaneously built a supporting professional knowledge base, including 64 policy documents, 226 typical service cases, and 30 sets of standard report examples. This allows frontline personnel to independently update and iterate the knowledge content, comprehensively ensuring the professionalism, accuracy, and practicality of the intelligent output.

Currently, this smart agent has been fully deployed in frontline operations, delivering significant improvements. Previously, writing investigation reports took several hours; now, staff only need to enter work order information and briefly describe the incident, a well-formatted, accurate, and well-supported standardized report can be generated in about 10 minutes, improving efficiency by more than 10 times.