不会我先用大概五到十分钟的时间吧跟大家介绍一下就是整个一个三季度的一个情况前三季度的公司的那个营业收入是57.4亿同比增长0.5%这个收入放缓的这个情况大家也看到了 实际上这个跟我们整个的一个受到就是第一就是外部环境的一个影响从六月份我们看到这个趋势是比较明显的啊这个有直接的一个关系然后第二个呢在整个一个宏观环境的影响下呢我们整个的一个行业化现在整个一个组织实际上已经到位了但是呢行业化的威力呢确实还没有发挥到就是我们原来预想到的这么一个水平应该说行业化的 呃这个整个的一个成效啊等会我们也会再介绍一下啊呃这里呢我们主要说一下就是这个收入增速放缓的那个两个原因啊呃我们也看到了那个余生收入呢还是继续保持着8.6%的一个增长啊订阅收入的增速呢就是更更高了啊28%左右的一个增速啊订阅合同负债呢有32%的一个增速这个也确实是在整个的一个 我们大中小特别是中端今年是全面订阅化把我们的U8软件现在基本上也是转为我们YS这样的一些订阅的产品对我们整个中端的软件收入有一个比较大的影响但是订阅这一块呢确实是继续走向我们的那个接近的走向我们的目标吧所以我们整个订阅的收入有一个比较好的增速 同时呢我们也看到了就是在效益化这一块啊我们的 ...

Investment Rating - The report does not explicitly state an investment rating for the industry or specific companies Core Insights - The global IT technology and industry innovation has entered an AI-centric era, with significant trends including the rapid expansion of AI and machine learning applications across various sectors, the development of cloud computing and big data technologies, and the rise of blockchain technology [2][3] - The era of AI popularization has arrived, marking a shift from exploration and innovative applications to widespread adoption, with AI becoming the core of industry innovation [3] - The comprehensive digital and intelligent business innovation era emphasizes both digitalization and intelligence, leading to a new stage of "smart" business practices [4] Summary by Sections AI-Centric Innovations - AI technology is transforming data processing and analysis, enabling industries to fully leverage big data and driving digital transformation [2] - The emergence of new business and service models driven by AI, such as personalized recommendations and intelligent customer service, enhances consumer experiences and economic growth [2] YonGPT Overview - YonGPT is a significant enterprise service model developed by the company, integrating various industry knowledge and business know-how to provide intelligent human-machine collaboration, business insights, and decision support [6][7] - The model focuses on four main application areas: intelligent business operations, natural human-machine interaction, knowledge generation, and semantic application generation [5][26] Core Advantages of YonGPT - The company has a rich history and experience in enterprise software and services, providing a strong knowledge base for YonGPT [8] - YonGPT offers comprehensive solutions across key business areas, enabling clients to meet multiple business needs on a single platform [8] - A strong R&D team dedicated to continuous innovation and improvement in AI applications supports YonGPT's deployment in enterprise scenarios [8] Application Scenarios - YonGPT has been applied in various business scenarios, including intelligent revenue and tax operation analysis, financial management systems, and talent discovery and recruitment [30][41] - The model enhances operational efficiency by providing intelligent solutions for business processes, risk identification, and opportunity recognition [30][31] - The integration of AI in financial management aims to transform traditional accounting processes into real-time, intelligent operations [32][36] Future Prospects - The report highlights the potential for YonGPT to evolve into a "TalentGPT," assisting enterprises in accurately identifying and managing talent through advanced data analysis and machine learning techniques [41][43] - The ongoing development of AI technologies is expected to further enhance the capabilities of YonGPT, making it a vital tool for enterprises in their digital transformation journeys [27][39]

Financial Data and Key Metrics Changes - The company reported a revenue growth of nearly 20% in Q1 2023, indicating a positive trend in its financial performance [3] - The company aims to improve its gross margin from 50 basis points last year to around 60 basis points this year [5] Business Line Data and Key Metrics Changes - The company has reduced its workforce by approximately 7% in Q1 2023, with expectations for a slight decrease in Q2 [7] - The company anticipates continued steady revenue growth in Q2, with a clearer trend of reduced losses [7] Market Data and Key Metrics Changes - The company has seen strong growth in sectors targeting state-owned enterprises, particularly local state-owned enterprises, despite macroeconomic pressures affecting consumer-related industries [8][9] - The company is preparing for a more rigorous operational strategy in response to potential economic downturns, aiming for stable growth [10] Company Strategy and Development Direction - The company is focusing on efficiency-driven operations and aims for steady revenue growth while improving profitability and cash flow [4] - The company is expanding its overseas business, particularly in Southeast Asia, North America, and the Middle East, with a new office established in Dubai [11] Management's Comments on Operating Environment and Future Outlook - Management acknowledges ongoing macroeconomic pressures but remains optimistic about the growth potential in the domestic and overseas markets [10][11] - The company is preparing for a challenging economic environment while also being ready to capitalize on better economic conditions [10] Other Important Information - The company is integrating AI capabilities into its products, with a focus on standardizing applications and reducing delivery costs [12][15] - The company has seen significant interest in its private model AI solutions, with a notable first order amounting to nearly 10 million [14] Q&A Session Summary Question: What is the current state of the bidding environment and order structure for Q2? - The company has seen good order growth in the 10 million range, although macroeconomic pressures have affected the bidding process, particularly for private enterprises [37] Question: What is the sales ecosystem like, particularly the ratio of direct sales to channel sales? - Direct sales dominate the large customer segment, while channel sales account for less than 20% of overall sales, primarily in small to medium-sized businesses [38] Question: What are the key R&D focus areas for this year? - The company is focusing on integrating more AI capabilities into its products and enhancing delivery capabilities with new versions of its software [31][32]

Summary of Conference Call Transcript Company and Industry - The discussion pertains to a company involved in the biotechnology sector, specifically focusing on genetic data and its applications in enhancing operational efficiency. Core Points and Arguments - The company has observed significant improvements in operational efficiency related to genetic data during the first half of the year, although comprehensive data for the second quarter is still pending [1] - In April, the company released a report indicating that its revenue experienced a rapid growth of over 12% year-on-year [1] Other Important but Possibly Overlooked Content - The lack of complete data for the second quarter may limit the ability to provide detailed insights into the company's performance in that period [1]

Industry Investment Rating - The report does not explicitly provide an industry investment rating [1] Core Views - Data is considered the "oil of the 21st century" and a core element of economic development in the digital economy era [6] - Data, as a production factor, can significantly enhance production efficiency when combined with other factors, creating a "multiplier effect" [7] - The integration of data into financial statements is a significant theoretical innovation in China's economic field, marking a shift from being "on the verge" to "inevitable" [9] - Central enterprises' data assets have immense potential and value in the digital economy era due to their extensive coverage, cross-industry integration, and high data quality [22][23] Policy Background and Significance - The 19th CPC Central Committee's Fourth Plenary Session in 2019 first included data as a production factor, reflecting its increasing importance in economic activities [7] - The "Data Twenty Articles" emphasize the need to promote data compliance, efficient circulation, and empowerment of the real economy, marking a significant step in data assetization [7] - The establishment of the National Data Bureau in 2023 further underscores the strategic importance of data in reshaping global economic structures [7] Central Enterprises' Data Assetization Challenges - **Data Value Mining**: Central enterprises face challenges in effectively mining and utilizing the rich commercial value embedded in their data assets [25] - **Data Governance**: The vast scale and diversity of data assets make governance complex, requiring robust systems for data standards, quality, and security [26] - **Data Security Risks**: High data security risks due to sensitive information such as trade secrets and personal data necessitate stringent security measures [27] - **Accounting Complexity**: The lack of clear paths for data asset formation and cost allocation poses significant challenges for accounting treatment [28] Central Enterprises' Data Assetization Path - **Data Scenarioization**: Identifying key business scenarios and data needs to lay the foundation for data resourceization and value realization [33] - **Data Resourceization**: Transforming raw data into reusable data resources through processes like cleaning, integration, and storage [35] - **Data Value Realization**: Discovering and leveraging the potential value of data through analysis, product development, and trading [36] Central Enterprises' Data Assetization Solutions - A dual-layer "Pagoda" value model is proposed, focusing on scenario-based data assetization and integration into financial statements [37] - The solution emphasizes the importance of data governance, cost allocation mechanisms, and the establishment of independent data management departments [38] Data Assetization Services - Services cover multiple key areas of data assetization, including value planning, resource management, and intelligent accounting [64] - Different service levels (basic, standard, advanced) are available to meet varying enterprise needs [65]