Nanjing Iron & Steel Co., Ltd. (NISCO), in collaboration with Huawei and ecosystem partners, has commercially deployed the world's first steel model powered by swarm intelligence—the YuanYe Steel Large Model—across multiple scenarios at scale. The announcement, made via Media OutReach Newswire, signals a major step in the industrial application of artificial intelligence, moving core steelmaking operations from reliance on human experience to data- and intelligence-driven collaboration.
The significance of this deployment lies in its proof that AI can be embedded into every core stage of a traditional heavy industry—ironmaking, steelmaking, rolling, and quality inspection—to create green and high-end “AI-powered super steel plants.” Unlike general-purpose monolithic models, YuanYe fuses multiple AI models with metallurgical mechanism models to form a dual-drive, multi-model cluster architecture: a “right brain” for probabilistic computing and a “left brain” for precise, scientific decision-making. This hybrid approach allows the system to handle the complexity and safety-critical nature of steel production while continuously learning from massive sensing data aggregated from millions of operational technology data points across 26 business domains.
The implications for the industry are substantial. NISCO reports that 100% of its key equipment is now connected and digitally controlled, new product research and development cycles have been shortened by 50%, and annual costs have been reduced by over CNY100 million (approximately US$15 million). By October 2026, the company had launched 25 business agents covering visual quality inspection, process optimization, production scheduling, and operations management, setting a new benchmark for digital and intelligent steel transformation.
Breakthroughs in four core scenarios illustrate the model's impact. In ironmaking, AI makes blast furnaces transparent, predicting temperatures and identifying issues two hours in advance with over 90% accuracy, increasing prime-grade molten iron yield by over 10% while cutting unit energy consumption. In rolling, the model achieves millisecond-level response, narrowing thickness tolerance to ±0.2 mm and reducing steel thickness deviation to 1.9%, with the rolling-force hit rate jumping from 88% to 98%. In quality inspection, an integrated smart metallographic system has doubled inspection efficiency, raising accuracy to over 95% and cutting per-sample inspection time from 10 minutes to 3–5 minutes. In energy and environmental control, the S-Link Intelligent Agent for Gas and Flue Gas Sulfur Control issues sulfur-risk warnings one hour in advance with over 95% accuracy, slashing natural gas co-firing consumption by nearly 50% and reducing downtime from emission exceedance by over 25%.
Beyond operational metrics, NISCO emphasizes a human-centric paradigm. Li Jinyan, General Manager of the Digital and Intelligent Integrated Development Department and Director of the AI Research Institute at NISCO, stated that the purpose of digital transformation is “not to replace people, but to unleash human potential.” To date, NISCO has deployed over 300 AI models alongside more than 1,000 low-code agents and lightweight applications built independently by frontline employees. As Cheng Yongfu, Senior Industrial Solution Expert at Huawei's Steel & Non-ferrous BU, noted, the real value of industrial AI is realized when it expands from single-point applications to comprehensive integration with production, operations, and management.
Looking ahead, NISCO plans to explore dedicated data centers for smart steel plants with Huawei and other partners, centered on an AI-native three-tier architecture and powered by YuanYe, aiming to provide a replicable and scalable benchmark for the global steel and manufacturing industries.
