China Construction Group's "Construction Industry Supply Chain High Quality Data Set" Selected as a Typical Case of National High Quality Data Set

On August 28, the National Data Bureau released a typical case of high-quality data set at the "High-quality Data Set Theme Exchange Activity" of the 2025 China International Big Data Industry Expo, and the "High-quality Data Set of Construction Industry Supply Chain" of China Construction Group was successfully selected. The high-quality data set of the supply chain in the

construction industry is built with the goal of "being directly used for artificial intelligence training", integrating the basic business information, performance credit information, material price information and recruitment information of 1 million suppliers in the cloud construction network, focusing on the key scenarios of the supply chain in the construction industry. It covers suppliers, commodities, engineering performance, construction, green building and other core business areas, and provides efficient and high-quality data support for the training of large model of construction supply chain. The data set has successfully passed the 4-level evaluation of AI data set quality, and is the first high-quality data set of central enterprises in the construction industry to pass the highest rating of AI data set. The data set supports the construction and application of a series of scenarios of intelligent procurement experts in Yunzhu Network, including intelligent sourcing, intelligent inquiry and building materials knowledge questions and answers, and derives intelligent tools such as online tender preparation and tender self-inspection, among which the tender self-inspection has been commercialized, with more than 60,000 + suppliers experiencing it first, generating nearly 220,000 professional test reports.

In the future, China Construction Group will continue to give full play to the advantages of the whole industry chain, rely on massive data in advantageous and characteristic business areas, continue to build high-quality data sets, promote the construction of a richer industry-level high-quality data asset system, support the rapid development of industrial artificial intelligence applications, and promote the intelligent transformation and upgrading of the construction industry.