From Checks to 10‑Second Zero‑Error: Baidu Shengsu Enables AI Core Business in Shenzhen Grid

In a Shenzhen substation, a smart inspection robot slowly passes by equipment, and its camera precisely captures a tiny defect—an insulator damage with a slight oil leak. Within seconds, the backend system automatically identifies the defect, fills all required information, and generates a complete assessment and handling recommendation; frontline staff only need to click “confirm”.

Traditional manual inspection requires operators to manually record device details, defect symptoms, and remediation suggestions, a process that can take dozens of minutes. Even when computer‑vision (CV) is added, it only solves the detection step; downstream data entry and decision making remain manual. AI agents, despite strong general capabilities, suffer from three key issues in enterprise settings: they act only as peripheral Q&A tools, their decision accuracy hovers at 80‑90% and they lack deep business understanding, making them unsuitable for core workflows.

To address these gaps, Baidu Intelligent Cloud unveiled the “Baidu Shengsu” enterprise data‑intelligence platform at the Create 2026 developer conference. The platform now spans more than 20 industries and offers over 370 relational and multimodal operators, raising agent accuracy in complex scenarios to 99% and moving agents from peripheral assistance to core production decisions.

The breakthrough comes from a dual‑track solution called “Context Engineering + System Engineering”. Context engineering builds three knowledge graphs: Business Map structures orders, goods, and equipment to let the agent grasp entity relationships; Business Logic Map encodes expert decision rules into machine‑executable form; Business Execution Map removes read‑only limits by enabling the agent to invoke APIs for ordering, returns, and workflow actions, thereby suppressing hallucinations.

System engineering supplies the safety backbone: resource abstraction, fine‑grained permission control, sandboxed execution, full‑link audit, forward simulation, and backward tracing ensure agents run securely and controllably.

In the Shenzhen Power Supply Bureau pilot, the platform models hardware assets, defect types, and handling rules, linking them tightly to the underlying database. When the robot captures a defect, the agent automatically searches the equipment ledger and similar historical defects, fills the reporting form autonomously, and generates a global assessment based on asset status and lifecycle. This not only “sees” the defect but also “understands” its business context—severity, past handling methods—guaranteeing absolute accuracy and consistency while cutting manual verification time by roughly 50%.

Beyond power, Baidu Shengsu is driving AI agents into manufacturing, retail, and new‑energy domains. In manufacturing, it eliminates material‑shortage false‑reports and compresses replenishment decision cycles to minutes; in retail, human‑machine collaboration provides differentiated evaluation standards and pinpoint root‑cause analysis; in new energy, it tackles massive unstructured data, achieving end‑to‑end supply‑chain visibility.

These results stem from Baidu’s two‑decade accumulation of big‑data and cloud‑native technologies. At Create 2026, Baidu AI Cloud announced a full‑stack AI infrastructure upgrade—enhancing chips, cloud, models, and bodies—to further cement AI as a new‑quality production force rather than a mere capability tool.