Enterprise Knowledge Search · Risk Management
Yilian Tongda needed a safer and more efficient way to help power-industry staff work with scattered standards, maintenance records, inspection documents and risk-control knowledge that were difficult to search and keep consistent.
Reported impact
Yilian Tongda built a reusable energy-industry assistant that improves compliance, maintenance search, safety execution and knowledge reuse without forcing customers to replatform existing systems.
Yilian Tongda used Baidu AI Cloud's Qianfan platforms to turn fragmented power-sector documents and operating records into a governed enterprise assistant. The architecture combines a retrieval-augmented generation layer, enterprise permissions, scenario constraints and agent-style integration so the system can work with text, tables, images, structured data and real-time information instead of only answering from one knowledge base. In the target workflow, employees query compliance rules, safety requirements, equipment drawings, calibration records and technical-supervision materials through a single assistant, while the agent layer connects to existing enterprise systems without invasive rework. This lets the platform serve multiple roles at once: it standardizes compliance knowledge, guides risk-control execution, exposes equipment diagrams for field maintenance, and converts archived documents into operational knowledge rather than passive storage. The result is a domain-specific copilot for energy operations rather than a generic chatbot.
Standards, records, drawings and enterprise-system data are indexed through the RAG layer; staff questions invoke the Qianfan-based assistant, which retrieves the relevant materials and returns governed answers inside the enterprise workflow.
Agent technology can connect seamlessly to existing enterprise information systems in a non-invasive way (original: 借助千帆平台的Agent技术，可无缝对接企业现有信息系统，以非侵入方式提供全业务智能助手).
Qianfan's RAG capabilities process text, tables, images, structured data and real-time information with enterprise permissions and security controls (original: 利用百度智能云千帆平台的RAG算法技术，可精准处理文字、表格、图片、结构化数据及实时信息……支持企业级权限管理、业务定制、安全防护和场景限定).
The target scenarios include compliance, safety-production requirements, maintenance drawings, calibration records and technical-supervision materials (original: 合规性挑战……安全生产管理挑战……设备检修挑战……热工仪表管理挑战……技术监督挑战).
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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