Core Viewpoint - The report from Zhongtai Securities maintains an "overweight" rating for Mingyuan Cloud, forecasting revenue and net profit for 2025-2027, while highlighting the company's resilience in the face of a declining real estate market [1] Revenue Performance - In H1 2025, the company reported a revenue of 606 million yuan, a year-on-year decrease of 15.9%, primarily due to the ongoing downturn in the downstream real estate and construction sectors [1] - The customer relationship management product line generated 383 million yuan in revenue, down 13.1% year-on-year, with the main product, Cloud Customer, achieving 377 million yuan, a decline of 5.1%, indicating some resilience [1] - The company increased its investment in AI-related products, with the Cloud Customer AI product signing contracts worth approximately 32 million yuan in H1 2025, surpassing the total for the entire year of 2024 [1] Cost Management and Profitability - The company has implemented lean operations to reduce costs and improve efficiency, particularly through the use of AI tools in customer service and R&D [2] - In H1 2025, sales, management, and R&D expenses were 317 million, 61 million, and 205 million yuan, respectively, showing year-on-year decreases of 22.2%, 56.5%, and 19.4% [2] - These efforts led to a net profit of 13.75 million yuan in H1 2025, with an adjusted net profit of 33.12 million yuan, marking a turnaround from losses [2] Business Outlook - For H2 2025, the company plans to focus on core products and key clients in the domestic market to enhance profitability, while reducing reliance on residential developers [3] - The company aims to increase investment in overseas markets, particularly in the Middle East and Europe, and establish localized teams to accelerate internationalization [3] - There will be a push for innovation in AI and SaaS products, with a focus on integrating AI technology into real estate business scenarios and exploring usage-based business models [3] - The company will continue to optimize resource allocation and talent management to enhance operational efficiency [3]