The platform's AI intelligent matching engine has been upgraded to Version 3.0, integrating large models and industrial knowledge bases. It adds an in-depth procurement scenario analysis function, which accurately predicts needs through buyers' multi-dimensional data, increasing the matching success rate by 42% and shortening the docking cycle from 48 hours to 12 hours.
On June 15, 2025, the "Zhilian Global · Construction Machinery Cloud Trade" platform officially launched the AI Intelligent Matching Engine Version 3.0, which achieves a qualitative improvement in supply-demand docking efficiency by reconstructing the algorithm model. Compared with the traditional "keyword + tag" matching mode, the new version deeply integrates large models and industrial scenario knowledge bases, realizing a core breakthrough from "passive response" to "active prediction."
The platform's technical director stated that Version 3.0 adds an "in-depth procurement scenario analysis" function, which can accurately identify potential demand preferences based on 12 types of multi-dimensional data such as buyers' historical orders, project types, and construction environments. For example, for buyers in tropical regions, the system will automatically prioritize matching construction machinery products with high-temperature protection configurations. Data shows that after the engine upgrade, the supply-demand matching success rate increased by 42%, invalid inquiries decreased by 58%, and the average docking cycle was shortened from 48 hours to 12 hours, significantly reducing manufacturers' screening costs.
