基于此，百融云创将公司级战略定位为"为客户提供交付结果的硅基员工"，在CX（Customer eXperence，客户体验）领域，百融云创产出对外创收硅基员工，覆盖智能营销、客户服务等场景，硅 基员工可完成精准触达、个性化推荐、复杂问题处理等任务。在EX（Employee eXperience，员工体 验）领域，可打造公司内部硅基员工，深入财务、税务、法务等专业服务环节，充当员工的"超级副 手"。 北京商报讯（记者 魏蔚）12月18日，企业级 AI Agent （智能体）公司百融云创发布企业级 AI Agent 战 略，提出 RaaS（Result as a Service，结果即服务） 商业模式，同时推出 Results Cloud（结果云） 与面 向多业务岗位的企业级 Agent 产品体系。百融云创创始人兼 CEO 张韶峰介绍："企业级 AI 的下一站， 不是更会说，而是更能做；不是交付一个功能，而是交付一个结果。" ...

Core Viewpoint - The competition in the enterprise-level AI Agent sector is intensifying, with major players leveraging their existing ecosystems and data advantages to deliver tangible value rather than just technological concepts [2][4][24]. Group 1: Market Dynamics - The enterprise-level AI Agent market is characterized by a "group fight" among major tech companies, including Alibaba's Lingyang, ByteDance's HiAgent 2.0, Baidu's Qianfan AgentBuilder, and Tencent's mixed multi-Agent framework, all targeting high-frequency business scenarios such as customer service and marketing [2][4]. - The recent surge in AI concept stocks, particularly Alibaba's announcement of a 380 billion yuan investment in AI infrastructure, has led to significant stock price increases, indicating strong market interest [4][24]. Group 2: Competitive Landscape - Palantir serves as a benchmark for enterprise-level AI Agents, utilizing a "data ontology" approach to unify disparate data sources and enhance operational efficiency [5][6]. - The role of "Forward-Deployed Engineers" at Palantir exemplifies the importance of integrating technical solutions with business strategy, ensuring that AI Agents are effectively embedded within client operations [6][7]. Group 3: Lingyang's Positioning - Lingyang, Alibaba's enterprise digital service company, has evolved from its origins in Alibaba's data platform, focusing on integrating data intelligence into various business processes [8][10]. - The launch of AgentOne marks a significant advancement, providing a comprehensive platform that enables businesses to create and deploy AI Agents tailored to their specific needs [10][11]. Group 4: Case Studies and Applications - The collaboration between Lingyang and Fosun Tourism demonstrates the practical application of AgentOne, where AI G.O enhances customer experience by providing seamless service throughout the travel journey [18][19]. - AI G.O's implementation has transformed the service model from reactive to proactive, significantly improving customer satisfaction and operational efficiency [19][22]. Group 5: Strategic Implications - Lingyang's approach emphasizes deep data intelligence and customer co-creation as essential elements for delivering business value and achieving market respect [24]. - As a critical component of Alibaba's strategy, Lingyang acts as the "last mile" in reaching enterprises and the "first stop" for businesses to experience and validate the value of AI Agents [24][25].

Core Insights - The narrative around large models has shifted towards enterprise-level AI Agents, focusing on the integration of AI into business processes and the creation of replicable, operational intelligent platforms [1] - Companies that can deliver measurable ROI through AI integration will be seen as the ultimate players in the market [1] Company Summaries 1. MaiFus (02556.HK) AI-Agentforce - MaiFus has focused on the "last mile" of enterprise AI application, emphasizing the concept of "delivery equals operation" for its AI-Agentforce platform, which highlights deployability, operability, and sustainable optimization [2] - The AI-Agentforce 2.0 integrates workflow orchestration, RAG knowledge engine, and DevOps lifecycle management, enabling efficient development and deployment of high-value AI applications [2] - The platform allows frontline staff to quickly generate and manage agents using natural language, reducing deployment barriers and accelerating AI application penetration within organizations [2][3] 2. ByteDance HiAgent - HiAgent is a highly platformized intelligent agent platform that aims to create a standardized, scalable operating system for AI agents, facilitating large-scale deployment and cross-scenario replication [4] - It features a unified agent orchestration framework that integrates a three-stage execution chain, supporting natural language, flowcharts, and API task flow construction [4] - HiAgent has been widely applied internally at ByteDance for tasks such as content review and customer service automation, and is gradually being offered as a SaaS product to external enterprises [4] 3. Dify - Dify is an active open-source intelligent agent platform that has gained traction in the GitHub community since its launch in 2023, primarily serving small and medium enterprises and AI developers [5] - The platform supports private deployment and a plugin ecosystem, allowing developers to build adaptable intelligent systems at low costs [5] - Dify is focused on creating a standardized open-source community to accelerate deployment efficiency for enterprises [5][6] Market Insights - MaiFus has chosen a challenging yet correct path by focusing on scene understanding, process re-engineering, and business closure rather than competing on computing power or model parameters [3] - HiAgent's strengths lie in its platform standardization and component-based development, which enhance system stability and reduce marginal costs for large-scale deployment [4] - Dify's lightweight platform is well-suited for sectors requiring private deployment, such as healthcare and government, due to its ease of deployment and strong controllability [6] Conclusion - The AI Agent market is diversifying, with companies like MaiFus focusing on value realization, while others like Baidu and Huawei pursue deep industry integration [7] - The ability to integrate AI with business processes and deliver measurable commercial value will determine the winners in this competitive landscape [7]

Summary of Conference Call Records Industry Overview - The conference call discusses the advancements in enterprise-level AI applications, particularly in the ERP (Enterprise Resource Planning) sector, highlighting the integration of AI technologies to enhance various modules such as finance, supply chain, CRM (Customer Relationship Management), and EPM (Enterprise Performance Management) [1][3][4]. Key Points and Arguments 1. **AI Enhancements in ERP Systems**: AI significantly improves ERP functionalities, with domestic systems leveraging deep learning algorithms to enhance operational efficiency and value creation [1][3]. 2. **Rapid Iteration of AI Products**: ERP systems are rapidly iterating AI products based on models like GPT-4 and domestic DeepThink, improving intelligent reception capabilities [1][4]. 3. **Challenges for Domestic ERP Vendors**: Domestic ERP vendors face challenges such as insufficient feature improvements and a market that demands practical solutions rather than mere technological hype [1][5]. 4. **Huawei's AI Integration**: Huawei integrates its DeepSeek model into its self-developed ERP system, enhancing management capabilities and planning to market this solution [1][8]. 5. **Oracle's Competitive Edge**: Oracle utilizes its Fusion ERP middleware, combining deep learning and GPT algorithms to provide decision support and maintain competitive advantages [1][9][10]. 6. **AI's Impact on Efficiency**: Implementing AI can significantly enhance efficiency across various business functions, including HR, marketing, sales, supply chain, and finance [1][11]. 7. **Differences in Domestic and International ERP Markets**: The international ERP market is more capitalized and performance-driven compared to the domestic market, which has unique challenges and growth rates [1][12]. 8. **Vertical Software Companies**: Vertical software companies in China, like Guodian NARI, perform well due to their specialized offerings and pricing power [1][13]. 9. **Oracle's AI for Fusion**: Oracle's AI for Fusion helps businesses unlock AI value through predictive modeling, anomaly detection, and actionable insights [1][14][15]. 10. **Dynamic Reporting Capabilities**: Oracle's management reports are dynamic, reflecting real-time data updates and supporting multiple workflows [1][16]. 11. **Unique Advantages of Oracle**: Oracle's products are based on Java, allowing for easier integration and faster deployment compared to competitors like SAP [1][24]. 12. **Client Base in China**: Oracle has a diverse client base in China, including major companies and government departments, utilizing localized ERP systems [1][29]. 13. **Challenges for Chinese Enterprises**: Chinese enterprises face challenges in data accumulation and require robust digital transformation to leverage AI effectively [1][32]. Additional Important Content - **AI Commercialization**: The call discusses how AI commercialization can be achieved by embedding AI technologies into enterprise models, with examples from Huawei and Oracle [1][6]. - **SAP's Market Exit**: SAP is exiting the Chinese market due to its product limitations and lack of localization, which does not meet the complex needs of Chinese enterprises [1][23]. - **Oracle's Service Quality Assurance**: Oracle has implemented a compensation mechanism for service disruptions, showcasing its confidence in product quality [1][31]. This summary encapsulates the key insights and developments discussed in the conference call, focusing on the impact of AI on the ERP industry and the competitive landscape among major players like Oracle and Huawei.