Investment Rating - The report maintains an "Outperform" rating for the computer industry, indicating a positive outlook compared to the broader market [3]. Core Insights - The report emphasizes the shift from traditional Software as a Service (SaaS) models to a results-oriented service model known as Results as a Service (RaaS), which ties service fees directly to measurable business outcomes [7][13]. - The adoption of RaaS is being accelerated by advancements in artificial intelligence (AI) and large model technologies, which enhance the ability of businesses to deliver measurable results [22][26]. - Companies that integrate deep industry knowledge and data into their AI solutions are expected to deliver higher returns on investment (ROI) and are recommended for investment consideration [51]. Summary by Sections 1. RaaS Model Accelerating Adoption - RaaS represents a fundamental shift in business logic, moving from paying for software usage to paying for tangible results [13][14]. - The report highlights successful international examples of RaaS implementation in sectors like fraud prevention and identity verification, showcasing its viability [26][29]. - Domestic companies are increasingly exploring RaaS, with AI driving the transition from providing tools to delivering results across various industries [7][38]. 2. Configuration Recommendations - Companies with strong data and industry expertise in AI applications, such as advertising and transaction facilitation, are likely to achieve higher ROI and are recommended for investment [51]. - Enterprise IT service providers whose products are deeply integrated with business systems are also positioned to transition to a results-based payment model, enhancing customer retention and willingness to pay [51].

Core Insights - The forum "AI + Traditional Industry" held in Shanghai highlighted the integration of AI technology into traditional industries, showcasing valuable experiences from companies like Zhaogang Network [1][3]. Group 1: AI Application in Traditional Industries - Zhaogang Network has established a production service system focused on the entire transaction process in the steel industry since its inception in 2012 [3]. - The company employs a dual strategy for AI application, developing its own industry-specific AI models while also collaborating with leading enterprises to enhance user experience and address technical issues [5]. - Zhaogang Network has developed 12 AI Agents and 4 flagship AI products that significantly improve efficiency across the entire sales process and internal management [3]. Group 2: Technological Advancements and Collaborations - The SaleMatch trading engine, developed by Zhaogang Network, has improved its message processing capacity to over 10 million messages daily with an accuracy rate exceeding 95% [3]. - The partnership with Tencent led to the establishment of Tengcai Technology, which has expanded its business from steel to other rapidly fluctuating industrial raw materials, demonstrating the cross-industry application of Zhaogang Network's AI capabilities [3]. - The forum featured representatives from major tech companies like Tencent, Alibaba, Baidu, and JD, indicating the significant influence of the event in the AI and traditional industry landscape [5]. Group 3: Future Prospects and Industry Impact - Zhaogang Network aims to be among the first companies to enter the "A2A" era, which encompasses "Agent to Agent," "Application to Application," and "Area to Area" interactions, facilitating AI capabilities throughout the supply chain [5]. - The practical achievements of Zhaogang Network serve as a reference for the deep integration of AI into traditional industries, contributing to the high-quality development of the Chinese economy [5].

Core Viewpoint - The article discusses the collaboration between 找钢集团 (Zhaogang Group) and 托克集团 (Trafigura Group) to establish a joint venture, 宗金汇 (Zongjin Hui), aimed at creating a comprehensive e-commerce platform for non-ferrous metals, leveraging AI technology and extensive industry resources [2][3][12]. Group 1: Joint Venture and Market Potential - 找钢集团 has signed a joint venture agreement with Lykos Holding Hong Kong Limited, investing 45 million yuan to establish 宗金汇, where it will hold an 8.57% stake [2]. - The collaboration aims to build a full-category e-commerce platform for non-ferrous metals, addressing the growing demand from customers who also have steel procurement needs [3][6]. - The non-ferrous metal market in China has surpassed 2 trillion yuan in 2023, with a projected production of 7.919 million tons for ten types of non-ferrous metals in 2024, reflecting a year-on-year growth of 3.4% [10]. Group 2: Technology and AI Integration - 找钢集团's AI infrastructure, developed from its steel trading platform, is expected to enhance cross-category capabilities, facilitating efficient transactions in the non-ferrous metals sector [7][8]. - The company has launched a B2B trading SaaS tool, "腾采通," which utilizes AI technology to analyze over 6.73 million business opportunities daily, covering more than 11 million SKUs and facilitating over 100 million transaction matches [7]. - The AI-driven solutions are designed to improve operational efficiency, with AI agents achieving over 95% accuracy in matching inventory and responding to quotes, significantly enhancing transaction efficiency [7]. Group 3: Industry Challenges and Solutions - The non-ferrous metals market faces challenges such as low online penetration (5% compared to over 20% for black metals), inefficiencies in traditional trading models, and high financing costs for small and medium enterprises [11]. - The joint venture aims to address these pain points by providing comprehensive services, including intelligent pricing, B2B payment solutions, and supply chain management, thereby enhancing operational efficiency for businesses in the sector [14][15]. - 宗金汇's development strategy includes leveraging托克's self-operated resources and integrating 找钢's infrastructure to enhance service capabilities for small clients and create a complete industry chain [16].