Through the collaborative work of seven major AI agents, from intelligent sampling plan formulation, automatic sample identification and standard matching, to compliance judgment and early warning of potential risks, an automated and intelligent closed-loop for food safety inspection is realized. This platform can not only significantly improve the efficiency and accuracy from sampling to report generation, but also proactively manage risks through prediction models, serving as the core tool for building a modern intelligent supervision system. "Sky-Air-Ground" integrated observation network. Develop precise irrigation and water-fertilizer decision-making models based on artificial intelligence and crop Evapotranspiration (ET).

Construct a full life cycle closed-loop management from order placement, sample circulation, task scheduling to test data entry. Built-in diversified industry standard report templates, supporting formula-assisted calculation and raw data traceability. Create an efficient, compliant and fully traceable digital business platform for laboratories.