Core Viewpoint - The "Intelligent Internet Action Plan (2026-2028)" aims to establish a modernized information and communication network in Shanghai by the end of 2028, achieving L4 high-level intelligent network standards as defined by international standards organizations [1] Group 1: Goals and Objectives - By the end of 2028, Shanghai's intelligent communication network system is expected to be initially formed, focusing on high-speed, low-latency, highly reliable, green, secure, and automated networks [1] - The plan includes a significant enhancement of wireless network intelligence, aiming for a wireless intelligence penetration rate of 60% [1] Group 2: Infrastructure Development - The number of 5G-A three-carrier aggregation base stations is projected to reach 35,000 [1] - The intelligent deployment of wired networks will see coverage rates for new or upgraded OLT stations, intelligent broadband gateways, intelligent OTN stations, AI agents in IP networks, and router intelligence all reaching 40% [1] Group 3: User Experience and Applications - The plan aims to enhance intelligent communication service experiences, with a target of 5 million new intelligent application users [1] - It includes the large-scale access of intelligent terminals such as AI cloud phones, AI cloud computers, AI glasses, 5G-A vehicle-mounted terminals, and 5G-A embodied robots [1]

Investment Rating - The report does not explicitly state an investment rating for the industry Core Insights - The communication industry is transitioning from 4G/5G/5G-A to 6G, marking the beginning of a new era of connectivity that empowers vertical industries such as industrial internet, smart grids, and intelligent transportation [4] - The development of self-intelligent networks (AN) is crucial, with a focus on integrating AI and intelligent agents to enhance network autonomy and operational efficiency [5][6] - The TM Forum's self-intelligent network white paper 7.0 outlines a framework for self-intelligent networks, emphasizing the need for structured methods to design and integrate intelligent agents across the network [14] Summary by Sections 1. Definition of Self-Intelligent Network Agents - Self-intelligent network agents (AN Agents) are defined as autonomous systems that make decisions based on their perceptions and goals without human intervention, categorized into digital assistants and self-closed-loop agents [13][14] 2. High-Level Architecture of Self-Intelligent Networks - The architecture focuses on a three-layer model with autonomous domain capabilities, emphasizing the need for collaboration between different layers and the integration of AI technologies [15][19] 3. Key Technologies and Development Directions - The report identifies critical technologies such as communication large models, digital twins, intelligent collaboration, and intelligent learning as essential for the functionality of self-intelligent network agents [34][41] 4. Building Large Models in Self-Intelligent Network Agents - The report discusses the importance of specialized, pre-integrated, and co-evolving large models to enhance the capabilities of self-intelligent network agents [17][18] 5. Interface Protocols for Self-Intelligent Network Agents - Various paradigms for integrating intelligent agents are explored, including A2A-T protocols that facilitate seamless communication between agents [19][24] 6. Standards Progress and Implementation Recommendations - The report emphasizes the need for a standardized ecosystem to support the interoperability of self-intelligent network agents across different vendors [23][24] 7. Transition from Traditional Networks to Self-Intelligent Network Architectures - The evolution towards self-intelligent network architectures is driven by the need for enhanced operational efficiency and the ability to manage complex network environments autonomously [26][27] 8. Huawei ADN Intelligent Agent Practices - Huawei's ADN practices demonstrate the application of intelligent agents in real-world scenarios, showcasing significant improvements in operational efficiency and fault management [10][11] 9. Future Outlook for Self-Intelligent Network Agents - The report anticipates a shift from high-value scenario autonomy to comprehensive network autonomy, enabling operators to achieve end-to-end management and improved service quality [7][9]

Core Viewpoint - The company plans to raise up to 662 million yuan through a targeted stock issuance, focusing on the development of OSS product platforms and intelligent network applications, aiming to strengthen its core business competitiveness and explore new growth opportunities in line with the digital transformation trend in the telecommunications industry [1]. Fundraising Details - The total investment amount for the projects is 6.813756 billion yuan, with the raised funds allocated as follows: 2.73 billion yuan for OSS product R&D and intelligent network applications, 1.6 billion yuan for intelligent scheduling management systems, 740 million yuan for next-generation digital home software-defined terminals, 1.21 billion yuan for the Shanghai R&D office center, and 340 million yuan for working capital [3][4]. - The issuance will target no more than 35 qualified investors, with a maximum of 31.2 million shares to be issued, accounting for 30% of the company's total share capital before issuance [3]. Project Allocation - 2.73 billion yuan will enhance 15 existing OSS products to improve automation and intelligence in network operations [4]. - 1.6 billion yuan will develop nine product modules, including a computing controller, to support the "East Data West Computing" strategy [4]. - 740 million yuan will introduce SDN technology for home gateway management, aiding telecom operators in upgrading their digital home services [4]. - 1.21 billion yuan will be used for the construction of the Shanghai R&D office center to improve the working environment and attract talent [4]. - 340 million yuan will optimize the capital structure and support business expansion [4]. Company Position - As a core supplier in the OSS field for telecom operators, the company has a strong foothold in the ICT management sector, serving major operators like China Mobile and China Telecom, with software development and technical services accounting for over 95% of revenue from January to September 2025 [4].

Investment Rating - The report does not explicitly state an investment rating for the industry Core Insights - The rapid development of artificial intelligence is profoundly changing production and lifestyle, driving the upgrade of 5G core networks to AI core networks. Leading operators are actively practicing the commercial monetization of 5G-A intelligent core networks and considering the evolution towards an intelligent native Agentic Core [7][21] - The report identifies six major trends in the evolution of core networks, which have generated significant impact in the industry [7] Summary by Sections Trend One: Experience Management - The exploration of experience management for commercial monetization is beginning to show results, with operators enhancing operational capabilities through intelligence. Over 60% of users are willing to pay for better experiences, making experience rights a core competitive trend for operators [9][30] - Leading operators are exploring how to convert network experience into profitable rights products, combining high-end packages with scenario-based acceleration services to enhance user loyalty and open new revenue channels [30][31] Trend Two: AI Calling - AI Calling helps operators build an exceptional basic calling experience, evolving from voice assistants to multi-modal general assistants, thus seizing the AI business entry point. Operators are leveraging their unique advantages, such as a large user base and trusted numbering systems, to create differentiated competitive barriers [10][60] - The integration of AI capabilities into the entire calling process is key to enhancing user stickiness and stabilizing average call duration [57][61] Trend Three: Autonomous Network Level 4 (AN L4) - AN L4 has become an industry consensus, with network stability and operational efficiency being core strategic goals for operators. The TM Forum has designated 2025 as the commercial year for AN L4, with leading operators beginning to formulate their strategies [11][69] - The introduction of "digital employees" based on intelligent agent technology is playing a crucial role in complaint handling and alarm processing workflows [11] Trend Four: Intelligent Private Networks - The evolution of 5G-A connectivity capabilities is accelerating the development of intelligent private networks, which serve as accelerators for digital transformation across various industries. The integration of AI capabilities into connectivity is essential for building a robust foundation for enterprise AI applications [12] Trend Five: Collaborative Network Operations - The integration of communication, sensing, and computing capabilities is expected to release suppressed traffic and activate intelligent computing services. The report highlights the growing demand for high-definition video and the need for operators to enhance their network capabilities to meet this demand [13] Trend Six: Telecom Cloud Evolution - The telecom cloud is evolving from traditional cloud infrastructure to AI-native infrastructure, enabling operators to transition from "connectivity pipelines" to "connectivity + intelligent computing." This evolution is crucial for supporting the comprehensive intelligence of operator networks [14] Trend Seven: Agentic Core - The trend of agentification in AI terminals and services is driving the agentification of network architecture, enhancing differentiated connectivity capabilities and creating new business paradigms for on-demand network usage. The global digital services market based on agentified networks is projected to exceed $2.5 trillion by 2030 [15]

Core Viewpoint - The 2025 China International Information Communication Exhibition (PT Exhibition) showcased Nokia Bell's AI-driven self-intelligent network operation solutions, emphasizing the transition towards fully autonomous networks [2] Group 1: Self-Intelligent Network Development - The evolution of self-intelligent networks ranges from Level 0 (fully manual operation) to Level 5 (completely autonomous operation) [2] - Chinese operators are currently at approximately Level 3.5, with some scenarios achieving Level 4, which still requires human supervision [2] Group 2: Key Pathways to Full Autonomy - The four key pathways to achieving fully autonomous networks include: 1. Trustworthy AI-Ready data, ensuring data quality and organization for AI [2] 2. Measurable fully automated processes, transforming operational models and eliminating process bottlenecks [2] 3. Evolving intelligent agents capable of reasoning, acting, and self-learning for accurate intent management [2] 4. Predictive "network twins" that provide real-time reflections of network status through holographic topology [2]

Financial Performance - In the first half of 2025, the company achieved operating revenue of 106.04 million yuan, a decrease of 19.16% compared to the same period last year [2][3] - The net profit attributable to shareholders was -43.04 million yuan, down 85.70% year-on-year [3] - The net profit after deducting non-recurring gains and losses was -44.06 million yuan, a decline of 71.40% compared to the previous year [3] Business Challenges - The decline in software development orders due to telecom operators' cost-cutting strategies negatively impacted revenue targets for the first half of 2025 [3] - The company is actively advancing the development of the next-generation OSS product platform to create more business opportunities [3] Project Updates - The Zhengzhou Airport computing power project is progressing steadily, with equipment procurement and network testing underway [4] - The project is expected to generate new business income over a five-year operational period once completed [4] Strategic Direction - The company maintains a clear operational strategy, focusing on customer value and integrated marketing efforts [4] - New projects, including the Zhengzhou Airport Intelligent Computing Center, are being executed, with significant progress in product development [4] Capital Raising - The company has initiated a private placement for 2024, pending approval from the Shenzhen Stock Exchange and the China Securities Regulatory Commission [6]

Core Insights - The launch of the all-domain integrated computing network scheduling platform and the first wide-area network model and multi-agent system marks a significant advancement in China's computing resource management and network operations [1][2] - The platform aims to connect regions with abundant computing resources to those with high demand, potentially reducing management costs for enterprises by 50% [1] - The AI automatic design toolchain for baseband circuits is expected to streamline the design process, reduce costs, and improve efficiency in communication systems [2] Group 1 - The all-domain integrated computing network scheduling platform utilizes three pioneering technologies to achieve integrated scheduling across the nation [1] - The platform has been tested in various sectors, including hospitals and schools, and is aligned with national initiatives like "East Data West Computing" [1] - The wide-area network model and multi-agent system can autonomously sense, maintain, and repair network issues, applicable in 27 typical network operation scenarios [1][2] Group 2 - The system, led by the Purple Mountain Laboratory in collaboration with Jiangsu Future Network Group, China Unicom, and Huawei, has achieved an overall intelligence capability level of L4 [2] - The goal is to reach L5 level, enabling a fully self-intelligent network that can be generated on demand [2] - The AI automatic design toolchain can reduce the area of baseband circuits by 70% while maintaining communication performance, significantly shortening the design iteration process to just a few hours [2] Group 3 - The advancements in baseband circuit design are expected to lower energy consumption and costs for enterprises, ultimately benefiting consumers with improved product performance at reduced prices [3]

Performance Forecast - The company expects a net loss attributable to shareholders of 40 million to 46 million yuan for the current reporting period, compared to a loss of 23.1757 million yuan in the same period last year [1] - The net loss after deducting non-recurring gains and losses is projected to be between 41 million and 47 million yuan, compared to a loss of 25.7039 million yuan in the previous year [1] - The basic earnings per share are expected to be a loss of 0.39 to 0.45 yuan per share, compared to a loss of 0.23 yuan per share in the same period last year [1] Communication with Auditors - The company has communicated with the accounting firm regarding the performance forecast and there are no discrepancies between the company and the auditors concerning the performance forecast [1] Reasons for Performance Variance - The company's operating income shows significant seasonality, with a higher proportion in the fourth quarter, while management, sales, and R&D expenses are incurred more evenly throughout the quarters, leading to losses in the first half of 2025 [1] - The decline in software development business orders due to telecom operators' cost-reduction strategies has impacted the revenue targets for the first half of 2025 [1] - The company is actively advancing the development of the next-generation OSS product platform to create more business opportunities for incremental revenue in OSS [1] - In the new computing power business, the company is in a rapid development phase, with related projects progressing orderly towards operational status to gradually realize revenue [1]

Core Insights - Huawei's data center autonomous network achieved an overall intelligence level of AN L3.9, with core business scenarios in "planning and configuration" and "application deployment and configuration" reaching AN L4 level, marking it as the first solution to pass EANTC L4 autonomous network testing [1][2] - The evaluation by EANTC, a recognized independent network testing organization, serves as a significant reference for assessing network product performance, reliability, and intelligence level [2] Group 1 - The autonomous network grading assessment focused on three key value scenarios: planning and configuration, application deployment and issuance, and monitoring and troubleshooting, analyzing four critical capabilities of autonomous networks [2] - Huawei's solution demonstrated high intelligence and reliability in data center network operations, aligning well with the goals of AN L4, especially as enterprises expand data centers due to AI/ML workloads and private cloud adoption [2][3] Group 2 - The autonomous network solution has been deployed at scale in industries such as finance and the internet, with plans for broader implementation across various sectors in collaboration with industry organizations and testing agencies [3]

Core Viewpoint - The global telecommunications industry is facing a "growth without revenue" bottleneck, where the increase in network traffic does not translate into corresponding revenue growth, leading to a "growth reduction" phenomenon [1][3]. Group 1: Industry Challenges - The traditional network service model is homogenized, failing to meet diverse market demands, resulting in a lack of differentiation between high-value and ordinary services [1]. - Operators are experiencing a "pipeline" dilemma, where the expansion of 5G networks does not yield proportional income increases [1]. Group 2: Differentiated Connectivity - "Differentiated connectivity" has become a consensus in the industry, focusing on using technology to identify the value of different services and providing customized network guarantees for high-priority applications [3]. - Singapore Telecommunications (Singtel) exemplifies this approach by offering tiered service packages based on user needs, transforming operators from mere traffic providers to "service value definers" [3]. Group 3: Programmable Networks and AI Integration - Ericsson views programmable networks as a core development goal for 5G-A, enabling dynamic network configuration based on business needs through software-defined networking (SDN) and network function virtualization (NFV) [5]. - The integration of AI is reshaping network management, transitioning from passive to proactive management, with AI acting as a "network brain" for autonomous decision-making [5][7]. Group 4: Ecosystem Development - Ericsson is building an open ecosystem to attract third-party developers, creating a "network as a service" economic model, with a RAN ecosystem comprising 56 members [8]. - The acquisition of Vonage and the establishment of Aduna aim to create a CPaaS ecosystem, addressing fragmentation in network capability and enhancing collaboration with developers [8]. Group 5: Future Outlook - Despite the commercial launch of 5G-A, challenges remain, including deployment strategy delays in some regions and low penetration rates of new terminals [9]. - Ericsson proposes a dual-track development strategy to enhance 5G-A capabilities while promoting end-to-end differentiated services, aiming to redefine the telecommunications industry's revenue model and digital infrastructure [9].