Financial Performance - The company's total revenue for the first half of 2025 was 88.97 million yuan, a decrease of 11.97% year-on-year [1] - The net profit attributable to the parent company was -38.04 million yuan, an increase of 17.36% year-on-year [1] - The gross profit margin improved to 30.48%, up 38.64% year-on-year, while the net profit margin was -45.67%, a slight improvement of 5.14% year-on-year [1] - Total expenses (selling, administrative, and financial) accounted for 45.46% of total revenue, an increase of 43.48% year-on-year [1] Cash Flow and Debt - The company reported a negative operating cash flow per share of -0.76 yuan, an improvement of 18.68% year-on-year [1] - The company’s cash assets are considered healthy, but the average operating cash flow over the past three years was -17.43% of current liabilities [3] - Interest-bearing liabilities increased significantly by 157.35% year-on-year, reaching 20.41 million yuan [1] Business Model and Market Position - The company has a historical median ROIC of 11.61%, but the worst year recorded a ROIC of -13.42%, indicating a fragile business model [2] - The company has experienced three years of losses since its listing, reflecting challenges in its business model [2] - The company focuses on data intelligence technology, developing solutions tailored to specific industry needs, which has received positive recognition from clients [4][5] Fund Holdings - The largest fund holding the company’s shares is the Xin'ao Core Technology Mixed A Fund, which has increased its holdings [4] - The fund manager has reported a significant annual increase of 112.71% in the fund's net value [4]

Group 1: Company Overview - The company initially conducted its own research to gather data due to limited data availability, but has since evolved to leverage data collection as a key service in the big data era, providing comprehensive data support to clients [2] - The core competitive advantage lies in the ability to quickly identify client needs and establish methodologies for model building, utilizing machine learning and natural language processing technologies [3] Group 2: Business Strategy and Model Development - The company is transitioning from manual data analysis to automated analysis, enhancing model innovation capabilities to address unique problems with tailored models [3] - The strategic development of software business focuses on modeling business experience, algorithm development, and software implementation [2] Group 3: Technology Implementation and Client Solutions - The company has developed responsive algorithm models for specific scenarios, such as the "12345 Government Service Hotline," which can be generalized to other service areas [4] - Various self-service analysis tools have been created, including visualization dashboards and automated reporting, to facilitate client analysis in both commercial and governmental sectors [4] Group 4: Knowledge Graph and Large Model Integration - The integration of knowledge graphs and large models enhances decision-making capabilities, addressing issues like high costs and low coverage in knowledge graph updates [5] - The company aims to leverage the combined strengths of knowledge graphs and large models to capture opportunities in sectors such as government, finance, and insurance [5] Group 5: Application of Knowledge Graphs - The experience in constructing ontologies in specialized fields can be adapted to civilian applications, improving policy recommendation accuracy in government sectors [5] - The knowledge graph technology accumulated in specialized fields will support the company's expansion into government, finance, and insurance sectors [5]