Core Insights - The traditional supply chain faces significant challenges due to the penetration of the digital economy and diversified consumer demands, including inventory imbalances from demand forecasting errors, data silos, high human dependency in core processes, and high barriers to AI technology implementation [1] - Shenzhou Holdings has developed an enterprise-level supply chain AI product named "Xiao Jin" to address these challenges, focusing on "full-link perception, intelligent decision-making, and scenario adaptation" [1] - "Xiao Jin" utilizes a unique "3+N" intelligent agent architecture, which includes three core agents (data assistant, decision assistant, customer assistant) and multiple specialized agents for specific work scenarios, enhancing efficiency and meeting specialized needs [1] Performance Metrics - In the peak order processing during the 2025 "Double 11" event, "Xiao Jin" achieved a 96% accuracy rate in order forecasting, a 280% increase in peak order processing speed, and a threefold increase in order creation efficiency [1] - Warehouse operations saw a 20% overall improvement in complex document picking efficiency and a 15% increase in packing efficiency, while the time for outbound handover was reduced by 1.4 hours [1] - Daily operations benefited significantly, with the data assistant improving data query efficiency by 90%, the decision assistant enhancing complex data analysis efficiency by 50%-70%, and the customer assistant reducing customer service workload by 50% [1] Strategic Vision - The successful implementation of "Xiao Jin" not only resolves the challenges of AI technology in the supply chain but also establishes a new model of full-link intelligent collaboration, transforming the supply chain from a "cost center" to a "value center" [2] - Shenzhou Holdings aims to deepen its "AI full-stack technology + value scenario empowerment" model, building a large-scale cluster of vertical intelligent agents and expanding the intelligent agent ecosystem in collaboration with partners [2] - The company is committed to integrating AI with the real economy, driving industrial upgrades, and providing end-to-end data intelligence solutions across various industries, thereby becoming a core enabler in the digital economy era [2]

12 月 29 日，在智通财经第八届投资年会暨科大硅谷硬科技投资生态大会上，神州控股（00861）凭借深厚的技术积淀、完整的 AI 全栈能力与丰富的行业落 地成果，成功入选 "新势力人工智能企业" 榜单。这一荣誉既是行业对其 "Data×AI" 战略深化落地的高度认可，更是对其以技术创新赋能供应链产业数智化 升级的充分肯定。 02 行业智能体落地释放实践价值 依托全栈技术能力，神州控股将 AI 深度融入垂直领域，打造了一系列可复制、高实效的智能体应用，让技术真正服务于产业升级。在智慧供应链领域，神 州控股深耕物流供应链领域 20 余年，以 "Data x AI" 战略为核心，构建起覆盖供应链全链路的智能解决方案。今年，公司基于 "AI for Process" 理念重磅推出 企业级供应链智能体 "小金"，将 AI 深度融入履约决策全流程，打造从数据洞察到智能执行的智慧供应链闭环，为客户提供高质量、高效率的履约服务。 数据中台层依托 "燕云" 产品，构建起覆盖数据采集、清洗、建模、运维与安全的多模态大数据治理能力。无缝整合数百种多源异构数据，同时借助数据标 注、数字化建模等技术，生成高质量、标准化的数据资源，为 ...

Core Insights - The logistics industry is undergoing a transformation driven by AI and automation, particularly highlighted during the "Double 11" shopping festival, which poses significant challenges for logistics operations [1][2] - The collaboration between Shenzhou Holdings' subsidiary KJ and UQI aims to address the "last 10 meters" of logistics through the integration of humanoid robots and intelligent systems [1][2] Group 1: Industry Challenges - The logistics sector faces labor shortages and operational efficiency bottlenecks, especially during peak periods like "Double 11," where labor demand can increase by 6 to 12 times [2] - Some logistics hubs experience cargo congestion due to insufficient manpower, impacting delivery timelines [2] Group 2: Technological Innovations - The partnership will leverage a "cloud brain + edge brain" dual-core technology architecture, with KJ providing a "smart brain" through its proprietary logistics models and UQI contributing execution capabilities via its robotic systems [2][3] - The goal is to develop humanoid robots capable of performing complex tasks in logistics environments, requiring advanced visual recognition and coordination algorithms [3] Group 3: Collaborative Efforts - The collaboration aims to create a "logistics embodiment intelligence laboratory" to tackle key technologies such as multi-modal cargo recognition and autonomous learning processes [5] - The joint efforts will also focus on establishing open communication protocols for logistics intelligent systems, facilitating collaboration across different brands and types of equipment [5] Group 4: Strategic Importance - This strategic partnership marks a significant milestone in the logistics industry's shift towards intelligent and automated operations, aligning with national economic development plans [6] - The collaboration is expected to contribute to the development of industry standards and promote a technology-driven transformation in logistics, moving from labor-intensive to technology-intensive operations [6]

Core Insights - The collaboration between Shenzhou Holdings' subsidiary KJ and UQI aims to create a new ecosystem of embodied intelligence in logistics, aligning with China's 15th Five-Year Plan to advance high-tech industries over the next decade [1][2] - The partnership will focus on three main areas: technology, application scenarios, and ecosystem development, including the establishment of a logistics embodied intelligence laboratory and the creation of intelligent logistics operation scenarios [1][2] Technology Development - KJ will provide the "smart brain" support through its self-developed "KingKoo Intelligent Chain" logistics supply chain model and "Little Gold" intelligent body cluster, integrating over 20 years of industry experience [2] - UQI will contribute its "execution terminal" capabilities with its self-developed robot operating system UPilot and core controller ACU, utilizing industrial mobile robots and autonomous logistics vehicles for high-precision physical tasks [2] Industry Impact - The strategic cooperation is expected to address labor shortages and operational efficiency challenges in the logistics sector, significantly contributing to the digital and intelligent transformation of the industry [2] - This partnership is seen as a practical demonstration of the forward-looking layout of embodied intelligence and future industries as outlined in the national development recommendations [2]

Core Insights - Shenzhou Holdings' subsidiary KJ and UBTECH's subsidiary UQI signed a strategic cooperation agreement at CeMAT ASIA 2025 to enhance logistics automation and intelligence [1][4] - The collaboration focuses on three levels: technology, scenario, and ecosystem, aiming to address key challenges in logistics such as labor shortages and operational efficiency [2][3] Technology Collaboration - The partnership will establish a "Logistics Embodied Intelligence Laboratory" to tackle critical technologies like multimodal cargo recognition [1][2] - KJ will provide a "smart brain" through its proprietary "KingKoo Intelligent Chain" logistics supply chain model and "Xiao Jin" intelligent agent cluster, leveraging over 20 years of industry experience [3] Scenario Development - The focus will be on creating unmanned logistics operation scenarios in sectors such as fast-moving consumer goods, beauty, IT, and 3C, aiming to overcome the "last 10 meters" bottleneck in warehousing [1][2] Ecosystem Building - The companies will jointly develop an open protocol for logistics intelligent agent communication and scheduling, and publish an industry white paper to foster a developer ecosystem [1][3] Strategic Alignment - This collaboration aligns with the Chinese government's 14th Five-Year Plan, emphasizing the development of future industries like embodied intelligence [4] - Shenzhou Holdings aims to integrate big data and AI technologies into its supply chain strategy, having formed strategic partnerships with 12 core clients and ecosystem partners by 2025 [3]

Core Insights - Shenzhou Holdings' subsidiary KJ and UBTECH's subsidiary UQI signed a strategic cooperation agreement at CeMAT ASIA 2025 to enhance logistics automation and intelligence [1][4] Group 1: Strategic Cooperation - The cooperation will advance in three areas: technology, scenario, and ecosystem [1] - A "Logistics Embodied Intelligence Laboratory" will be established to tackle key technologies such as multimodal cargo recognition [1] - Focus industries include fast-moving consumer goods, beauty, IT, and 3C, aiming to create unmanned logistics operation scenarios [1] Group 2: Technological Framework - The partnership will leverage a "Cloud Brain + End Brain" dual-core technology architecture to address labor shortages and operational efficiency issues in the logistics sector [3] - KJ will provide the "smart brain" support with its self-developed "KingKoo Intelligent Chain" logistics supply chain model and "Little Gold" intelligent agent cluster [3] - UQI will contribute its "execution terminal" advantages through its self-developed robot operating system UPilot and core controller ACU [3] Group 3: Strategic Goals - Shenzhou Holdings positions supply chain scenarios as a core strategic focus, integrating big data and AI technologies [3] - By 2025, the company aims to establish strategic partnerships with 12 core clients and ecosystem partners, creating a competitive supply chain ecosystem [3] - The ongoing "Datax AI" strategy emphasizes high-quality data and AI technology to drive intelligent upgrades across the supply chain [3] Group 4: Policy Alignment - This collaboration responds to the Central Committee's call for forward-looking layouts in future industries such as embodied intelligence [4] - The joint innovation model of "technology co-construction + scenario co-creation + ecosystem sharing" aims to establish a benchmark for intelligent supply chain operations [4]

Group 1: AI Applications and Industry Integration - The AI large model technology is transitioning from exploration to industrial integration, with Agents being a key driver for efficiency in business scenarios [1] - The supply chain is identified as a critical area for AI application, where collaboration across companies and industries is essential for maximizing value [1][2] - The challenge lies not only in technology but also in transforming it into collaborative actions across various sectors [1] Group 2: Current Challenges in AI Implementation - A report from MIT indicates that while 90% of employees use general large models, only 5% of companies achieve measurable commercial returns, leading to the phenomenon known as "shadow AI" [2] - The disconnect between general large models and specific business needs hampers effective problem-solving and implementation [2] - Companies face significant challenges in inventory management and sales forecasting, necessitating a shift from reactive to predictive solutions supported by AI and big data [5] Group 3: Future Trends and Opportunities - The global generative AI market is projected to reach $10 trillion, driven by the urgent need for intelligent transformation across industries, particularly in supply chains [4] - AI and big data applications are expected to enhance seamless connections in cross-border e-commerce, international logistics, and digital certification, providing a solid digital foundation for global value chain participation [3] - The focus of industry competition is shifting towards "AI application craftsmanship," emphasizing the need for practical industrial applications that address real business problems [5] Group 4: Talent Development and Data Integration - There is a pressing need for talent in the field of supply chain management and big data, with educational institutions aligning their programs to meet industry demands [6] - Initiatives to break down data silos and establish cross-departmental and cross-industry data flow mechanisms are being promoted to enhance technology application in logistics and transportation [6]

Core Insights - The launch of the self-developed supply chain intelligent agent "Xiao Jin" by Digital China Holdings' subsidiary, KJ Supply Chain, aims to enhance efficiency in data querying, intelligent decision-making, and customer service [1][2] - The global generative AI market is projected to reach $10 trillion, indicating a strong demand for intelligent transformation across industries, particularly in supply chains [2] Group 1 - "Xiao Jin" is part of Digital China's ongoing "Data x AI" strategy, leveraging the Yanyun Infinity platform to empower core supply chain business scenarios [1] - The intelligent agent has shown significant improvements in order completion rates, warehouse management efficiency, and a reduction in customer complaints during its deployment at KJ's flagship warehouse in Kunshan [2] - The core issue with general large models is their disconnect from actual business needs, which "Xiao Jin" aims to address by integrating industry-specific knowledge and real-time business data [1][2] Group 2 - The development of "Xiao Jin" is based on over 20 years of operational experience and technical reserves, enabling it to understand logistics data and industry pain points effectively [2] - The future competition in the AI space will focus on the ability to industrialize applications that solve real business problems, rather than just the capabilities of large models [2] - KJ Supply Chain plans to collaborate with logistics companies, e-commerce platforms, and manufacturers to expand the ecosystem of supply chain intelligent agents, leading to a new era of "full-link intelligent collaboration" in the supply chain industry [3]