Company Overview - Beijing Haitai Ruisheng Technology Co., Ltd. was established on May 11, 2005, and listed on August 13, 2021. The company is located at No. 1 Building, 4th Floor, 68 Zhichun Road, Haidian District, Beijing. Its main business involves the research, design, production, and sales of AI training data [1]. Financial Performance - For the period from January to March 2025, Haitai Ruisheng achieved operating revenue of 69.81 million yuan, representing a year-on-year growth of 71.75%. The net profit attributable to the parent company was 371,600 yuan, showing a significant increase of 158.60% year-on-year [2]. - As of March 31, 2025, the company had a total of 12,500 shareholders, a decrease of 0.35% from the previous period. The average number of circulating shares per person increased by 0.35% to 4,813 shares [2]. Shareholder and Dividend Information - Since its A-share listing, Haitai Ruisheng has cumulatively distributed cash dividends amounting to 57.50 million yuan, with 46.80 million yuan distributed over the past three years [3]. - As of March 31, 2025, among the top ten circulating shareholders, the Noan Active Return Mixed A Fund (001706) was the ninth largest shareholder, holding 315,100 shares as a new shareholder [3]. Trading Activity - On August 25, Haitai Ruisheng's stock price fell by 0.39%, with a trading volume of 423 million yuan. The financing buy-in amount for that day was 53.94 million yuan, while the financing repayment was 51.11 million yuan, resulting in a net financing buy-in of 282,290 yuan. The total financing and securities balance reached 311 million yuan [1]. - The financing balance of 311 million yuan accounts for 3.89% of the circulating market value, which is below the 40th percentile level over the past year, indicating a relatively low position [1]. - On the same day, there were no shares repaid or sold in the securities lending market, with the securities lending balance also at zero, which is above the 70th percentile level over the past year, indicating a relatively high position [1].

Core Viewpoint - The company has signed an ecological cooperation agreement with Shenzhen Computing Science Research Institute to enhance its AI medical model business through collaboration in data quality and analysis [1][2] Group 1: Strategic Cooperation - The agreement aims to leverage the advanced technologies developed by the Shenzhen Computing Science Research Institute in database systems, data quality systems, and data analysis systems [2] - The collaboration will create a closed-loop ecosystem of "data governance + model iteration + scenario implementation" [2] - This partnership is expected to provide comprehensive data services, including data cleaning, intelligent analysis, and customized model training for clients in the healthcare sector, government departments, and industry AI applications [2] Group 2: AI Medical Model Development - The company is focusing on the development of AI medical models, which require high-quality, secure, and available medical big data as core support [1] - The medical data encompasses various forms such as medical records, imaging, and laboratory reports, necessitating high precision in data cleaning and labeling [1] - The collaboration is anticipated to accelerate the optimization and commercialization of the company's AI medical models, enhancing its core competitiveness in the AI healthcare sector [2]

Core Insights - The article discusses the evolution and significance of AI Data Services, emphasizing the shift from manual data collection to automated and intelligent data processing solutions [3][5][8]. Group 1: AI Data Services Overview - AI Data Services encompass the entire data support process required for AI system development, including data collection, cleaning, annotation, and delivery [3]. - The focus of AI development is shifting from model optimization to enhancing data quality, which is crucial for suppressing hallucinations and improving outputs [3][5]. Group 2: Evolution of AI Data Services - Initially, AI Data Services relied heavily on manual data collection and annotation through crowdsourcing platforms [5]. - The industry is now moving towards automation and platformization, utilizing algorithms for automatic annotation and data quality control technologies [5][6]. Group 3: Service Models in AI Data Services - Three primary service models are identified: Automated Annotation, Professional Data Annotation, and Full-Stack Services, each with distinct methodologies and target applications [7]. - Automated Annotation focuses on efficiency and algorithm assistance, suitable for large-scale tasks, while Professional Data Annotation emphasizes high accuracy in specialized fields [7]. Group 4: Industry Structure - The AI Data Services industry chain consists of upstream data acquisition and processing tool providers, midstream data service providers, and downstream application scenario clients [8][9]. - Upstream players include data collection devices and annotation platforms, while midstream companies handle data processing tasks, and downstream clients span various industries like autonomous driving and healthcare [8][9]. Group 5: Market Trends and Financing - The financing landscape for AI Data Services has shown a "fluctuating rise followed by stabilization" trend from 2019 to 2024, indicating a maturing industry influenced by technological advancements and market cycles [9]. - Notable companies in the sector, such as 尚跃智能 and 博登智能, are expanding their service offerings and securing significant funding to enhance their capabilities [10][13][15]. Group 6: Recent Developments - Major investments in AI infrastructure are being made by global tech giants, such as Amazon's commitment of AUD 200 billion for data center expansion in Australia [22]. - Meta is negotiating a significant investment in Scale AI, highlighting the increasing importance of data annotation services in AI development [22].