Core Viewpoint - Tianrun Cloud (02167.HK) experienced a significant increase in stock price, rising over 27% in early trading and currently up 25.18% at HKD 6.81, with a trading volume of HKD 10.2028 million [1] Group 1 - The stock price of Tianrun Cloud surged by more than 27% in early trading [1] - As of the latest update, the stock is up 25.18% and priced at HKD 6.81 [1] - The trading volume reached HKD 10.2028 million [1]

在AI浪潮席卷各行各业的当下，几乎所有企业管理者都已经意识到：AI将是未来竞争的关键。 几乎所有人都在思考，如何才能尽快推动企业从传统的"人力驱动"转型为"AI驱动"，抓住"人口红利"到"AI红利"的历史机遇。 然而，真正落到实践层面，问题却变得复杂：企业的业务庞杂、流程繁多，转型远不是一句口号。许多管理者虽然知道"AI转型迫在眉睫"，但具体该如何 转？从哪里先下手？往往陷入困境，一筹莫展。 因此，对于许多企业而言，当下最核心的问题不是"要不要用AI"，能否找到那个能同时满足「价值确定性」和「场景适配性」的最佳战略支点。 在众多业务环节中，客户联络正是那个可立即点燃价值飞轮的起点：数据天然在线、流程高度标准化、结果可清晰量化。它不仅能让AI价值迅速可见，更 能成为企业全局转型的战略支点。 为什么说客户联络是企业AI转型的最佳起点？ 原因很简单：它既直通企业核心价值，又具备天然的AI适配条件，还能快速消除转型焦虑。 首先，客户联络是最接近现金流的环节。无论是售前咨询、销售转化，还是售后服务与客户留存，每一次对话都直接关系到收入和口碑。AI在这里落地， 价值转化是立竿见影的：转化率提升、获客成本下降、客户体验改善 ...

Core Insights - The competition in the 3C home appliance market has intensified, with minimal differences in product performance and extreme price wars, leading consumers to take a more proactive approach in their purchasing decisions [1][2] - The shift in competition has moved from traditional advertising to engaging in meaningful dialogues with consumers, emphasizing the importance of pre-sales service in converting potential buyers [2][3] Consumer Behavior Changes - Consumers are now more knowledgeable and perform extensive research before making a purchase, often completing 80% of their decision-making process online through reviews, comparisons, and social media [1][2] - The nature of consumer inquiries has evolved from basic questions to more detailed and specific ones, reflecting their increased expertise and personalized needs [3][5] Service Expectations - Brands must adapt to the new consumer expectations by providing personalized and professional pre-sales service, moving beyond simple FAQ responses to more engaging and informative interactions [5][10] - The demand for a "scene expert" who can understand and design tailored solutions for consumers is rising, highlighting the need for emotional connection and trust in the purchasing process [5][12] ZENAVA's Role - ZENAVA is positioned as an AI pre-sales consultant that understands products, users, and scenarios, offering a more interactive and personalized service experience [6][12] - It utilizes a private knowledge base and advanced AI capabilities to provide comprehensive responses and recommendations based on user profiles and preferences [6][7] Service Transformation - The introduction of ZENAVA signifies a shift from traditional customer service to a more consultative sales approach, focusing on understanding, planning, and guiding consumer decisions [10][11] - This transformation allows companies to enhance service efficiency, reduce costs associated with customer inquiries, and improve overall customer experience [11][12]

Core Insights - The customer service industry is undergoing a quiet revolution, transitioning from a labor-intensive model to one driven by AI technology [1][2] - AI is transforming customer service roles from "firefighters" to "business experts," significantly enhancing customer experience and operational efficiency [2] Group 1: Traditional Customer Service Challenges - Traditional customer service involved repetitive tasks such as filling forms and cross-system operations, leading to low efficiency and customer satisfaction [1] - Customers have become frustrated with robotic responses and frequent transfers to human agents, resulting in a loss of patience [1] Group 2: AI Transformation in Customer Service - AI assistants can automatically generate work orders and conversation summaries, allowing agents to focus on verification rather than manual entry [5] - The process of creating FAQs has been streamlined; previously, it took about a month to compile thousands of FAQs manually, but AI can now automate this process [8][12] - AI can personalize responses based on the company's knowledge base, significantly improving the problem resolution rate compared to traditional text-based robots [15][17] Group 3: Operational Efficiency with AI - AI enables agents to perform cross-system operations with simple verbal commands, reducing time costs associated with complex tasks like logistics and membership inquiries [21][23] - The knowledge recommendation feature of AI helps alleviate the training burden on agents by suggesting relevant information during customer interactions [27][30] - AI can guide agents through service processes, standardizing workflows and minimizing errors, especially for new staff [33][36]

Core Insights - The article discusses the challenges of traditional return and exchange processes in customer service, highlighting the reliance on human intervention and the inefficiencies that arise from it. The introduction of ZENAVA, an AI-driven productivity platform, aims to transform this landscape by automating and streamlining the return and exchange process, thereby enhancing customer experience and operational efficiency. Group 1: Challenges in Traditional Return and Exchange Processes - The return and exchange process is heavily reliant on human intervention, with over 90% of users requesting human assistance when faced with these issues [1] - Traditional customer service systems struggle with complex return scenarios, leading to poor service experiences and inefficiencies during peak times [3][4] - A significant increase in return inquiries, such as a 300% surge during promotional events, places immense pressure on human customer service representatives [3] Group 2: ZENAVA's Innovative Solutions - ZENAVA is designed to handle the entire return and exchange process, from understanding customer intent to completing the transaction, effectively acting as an AI employee [1][3] - The platform features advanced intent recognition capabilities, allowing it to understand vague customer expressions and initiate appropriate processes [4] - ZENAVA supports image recognition, enabling customers to upload photos of products, which enhances the accuracy of return assessments [7] Group 3: Automation and Efficiency - The ZENAVA agent automates the return process, proactively guiding customers through various steps without waiting for user prompts, thus improving service efficiency [7][9] - The system can handle complex scenarios, such as late return requests, by clearly explaining platform rules and addressing customer emotions [9] - By automating standard processes, ZENAVA allows human employees to focus on strategic and complex decision-making, significantly improving service efficiency and organizational resilience [9]

Core Insights - AI is fundamentally reshaping the operational logic of businesses, transitioning from a human-centric model to an AI-driven approach [1][2][3] - Companies that have embraced AI early are experiencing significant improvements in customer service, marketing conversion, and operational efficiency [2][6] Group 1: Challenges of Human-Driven Models - Traditional human-driven organizational structures are increasingly revealing issues such as high costs, low efficiency, and slow response times [2][3] - In customer service, reliance on large teams leads to inefficiencies, with management layers and communication chains causing delays and reduced customer satisfaction [3][5] - The marketing sector faces similar challenges, where human-driven sales processes result in uneven lead distribution and low conversion rates, hindering growth [5] Group 2: Advantages of AI Employees - AI employees can autonomously handle over 80% of standardized customer service inquiries, allowing human agents to focus on complex issues, thus improving response times significantly [6][11] - In marketing, AI employees can independently engage customers, recommend solutions based on historical data, and efficiently manage leads, directly impacting revenue growth [6][8] Group 3: Organizational Transformation - Transitioning to an AI-driven model requires a complete restructuring of business processes, such as simplifying customer service hierarchies from three layers to two, enhancing efficiency [11][12] - The organizational structure shifts from "human managing humans" to "human managing AI," leading to a reduction in team sizes and a flatter organizational hierarchy [12][14] - Functional departments must also adapt, with traditional training roles evolving into knowledge management teams that focus on structuring information for AI utilization [14][15] Group 4: Strategic Imperative - The shift from human-driven to AI-driven operations is not merely an upgrade but a necessary strategic transformation for companies to remain competitive [8][15] - Future competition will hinge on the effectiveness of AI as a productivity engine rather than the number of human employees [15]

Core Insights - AI is transitioning from "technology proof of concept" to "scaled industrial implementation," with many companies embracing AI but struggling to create measurable business value [1] - The key challenge lies not in the AI technology itself but in the ability of companies to transform AI from "capability" to "productivity" [1] - Deep collaboration between technology and business is essential to unlock AI's potential [1] AI Applications - Customer service and marketing are identified as optimal entry points for AI transformation due to their ease of implementation, broad demand, and quick results [1][2] - To maximize AI's value, companies must integrate AI deeply into business processes, shifting from "human-driven" to "AI-driven" operations [1][2] Role of AI Trainers - AI trainers play a crucial role in teaching AI the business process logic, judgment systems, and language nuances necessary for task completion [2] - As AI employees gain business understanding and contextual adaptability, they can exhibit human-like warmth and intelligence, transforming customer service from a cost center to a value center [2] - Companies that successfully implement AI are establishing significant competitive barriers in customer service and marketing, making AI trainers highly sought-after talents [2] AI Trainer Development - Tianrun Rongtong has launched an elite AI trainer program to help companies quickly build AI-driven production capabilities, enhancing efficiency and growth [3] - The program focuses on practical skills and strategic value in the AI era, presenting a timely opportunity for businesses [3] Expertise and Training - The company boasts professionals with extensive experience in AI and software, leading various AI project implementations and upgrades for numerous listed companies [6] - AI trainers are dedicated to providing professional AI training and consulting services, assisting clients in achieving technological empowerment and business growth [9] Training Program Features - The training program features a "learn-practice-evaluate-apply" four-dimensional closed-loop design, significantly improving training conversion rates [10] - Participants will gain a comprehensive knowledge system for rapid internal retraining within their organizations [11] - Successful outcomes will be included in Tianrun Rongtong's official client case library, fostering a continuous mutual support network among industry peers [12]

近年来，客户联络行业受到哪些技术驱动因素的影响？ 客户联络行业是一个长周期的行业，从全球范围来看，主要应用在客服、电话 营销、售前咨询和商品推荐以及贷后催收催缴四大场景。过去 35 年，这些场 景一直存在，但其格局不稳定，受技术影响较大。在过去十年里，云计算成为 主要的技术驱动力量，包括基础设施云化和通讯资源云化。这两个轨道交叉促 进了中国业务量的快速增长，使企业规模得以扩大。此外，SaaS 形态也在这 十年内逐渐普及，我们公司作为 SaaS 形态的受益者，目前绝大部分收入都是 订阅制的循环性收入。 中国客户联络行业与美国同类行业相比有哪些特点？ 中国客户联络行业在过去十年经历了快速发展，但也面临严重内卷问题。尽管 业务量和客户数量突飞猛进地增长，但价格却急剧下降，目前价格仅为十年前 天润云 20251010 摘要 中国客户联络行业内卷严重，业务量和客户数激增，但价格大幅下降， 仅为十年前的 8%，导致企业规模受限，员工效率提升空间触顶，客服 人员流失率高。 客户联络市场格局趋于稳定，Agent 发展带来重构机会，AIGC 赋能 SaaS，从提升人的效率转向 AI 直接替代人，对管理软件赛道产生深远 影响。 ...

股份發行人及根據《上市規則》第十九B章上市的香港預託證券發行人的證券變動月報表 截至月份: 2025年9月30日 狀態: 新提交 FF301 致：香港交易及結算所有限公司 公司名稱: 天润云股份有限公司（於開曼群島註冊成立的有限公司） 呈交日期: 2025年10月6日 I. 法定/註冊股本變動 | 1. 股份分類 | 普通股 | 股份類別 | 不適用 | | 於香港聯交所上市 (註1) | | | 是 | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 證券代號 (如上市) | 02167 | 說明 | | | | | | | | | | | 法定/註冊股份數目 | | | 面值 | | | 法定/註冊股本 | | | 上月底結存 | | | 500,000,000 | USD | | 0.0001 | USD | | 50,000 | | 增加 / 減少 (-) | | | 0 | | | | USD | | | | 本月底結存 | | | 500,000,000 | USD | | 0.0001 | USD | | 50, ...

（於開曼群島註冊成立的有限公司） 股份代號 : 2167 2025 中 報 科技賦能 成就客戶 目 錄 公司資料 2 財務摘要 4 業務回顧、業務概覽及業務前景 5 管理層討論及分析 9 企業管治及其他資料 16 中期簡明綜合損益表 28 中期簡明綜合全面收益表 29 中期簡明綜合財務狀況表 30 中期簡明綜合權益變動表 32 中期簡明綜合現金流量表 34 中期簡明綜合財務資料附註 36 釋義 48 技術詞彙表 52 公司資料 董事會 執行董事 吳強 （首席執行官）（主席） 潘威 李晉 安靜波 （已於2025年3月28日辭任） 獨立非執行董事 翁陽 李鵬濤 李志勇 審計委員會 李志勇 （主席） 李鵬濤 翁陽 薪酬委員會 李鵬濤 （主席） 李志勇 吳強 提名委員會 吳強 （主席） 李鵬濤 翁陽 總部及中國主要營業地點 中國北京市 北京經濟技術開發區 榮華南路 2號院1號樓28-29層 環境、社會及管治（「ESG」）委員會 吳強 （主席） 潘威 翁陽 聯席公司秘書 王歡 呂穎一 授權代表 吳強 呂穎一 核數師 安永會計師事務所 註冊會計師及 註冊公眾利益實體核數師 香港鰂魚涌英皇道979號 太古坊一座27樓 註冊 ...