Core Viewpoint - Q-tech preannounced a significant net profit growth of 150-180% YoY for 1H25, with a mid-point of RMB305 million, surpassing Bloomberg consensus by 20% and tracking 54% of the FY25E net profit estimate [1][2]. Financial Performance - For 1H25, Q-tech's estimated revenue and net profit growth were 7% and 162% YoY, respectively, driven by a 2% YoY increase in CCM (with non-mobile CCM up 97%) and a 100% YoY increase in FPM (with ultrasonic FPM up 20x) [2]. - The gross profit margin (GPM) improved to 7.1% in 1H25, compared to 5.2% in 1H24 and 6.9% in 2H24, attributed to HCM spec upgrades and higher-margin non-mobile CCM and ultrasonic FPM shipments [2]. Outlook - The outlook for 2H25 is positive, with expectations of continued strong momentum driven by high-end smartphone camera upgrades (OIS/periscope), IoT/auto CCM growth, and GPM recovery [2]. - Revenue and net profit are estimated to grow by 25% and 162% YoY in 2H25E, respectively, supported by a 23% mix of high-end HCM in 2H and an 85% revenue increase in IoT/auto [2]. Earnings Estimates - The company raised FY25-27E EPS estimates by 21-30%, reflecting strong 1H25 performance and improved GPM outlook for FY26/27E, with EPS now 14-19% above consensus [1][3]. - The new target price (TP) is set at HK$13.21, based on a higher 19.5x FY25E P/E, aligning with the 10-year historical average forward P/E, following sector re-rating and a stronger outlook for FY26-27E [1][3]. Investment Thesis - Q-tech is positioned to capture high-end smartphone camera upgrade demand and momentum in IoT/auto CCM modules, leading to a reiteration of the BUY rating [3].

Core Viewpoint - The year 2025 is expected to be a pivotal year for the implementation of AI applications, with AI Agent scenarios poised for rapid growth, particularly in management software, where traditional industry leaders hold significant advantages [1][7]. Group 1: AI Agent Development - AI Agents are expected to accelerate their implementation due to advancements in technology and shifts in supply and demand, enabling autonomous planning, perception, decision-making, and execution capabilities [1][2]. - The value discovery on both the scenario and product sides is driving the rapid adoption of AI Agents, with clear ROI expected to facilitate AI application deployment [2]. Group 2: Optimal Scenarios for AI Agent Implementation - Management software is identified as one of the best scenarios for AI Agent deployment, driven by the need for improved labor efficiency and streamlined processes [3]. - A closed data loop enhances model capabilities and data security, with 59% of enterprises storing internal data within their environments, providing a solid foundation for model training [3]. - Business integration through reusable module interfaces reduces deployment costs and enhances service capabilities, allowing for faster application deployment [3]. - The trend of cloud transformation in management software aligns with AI functionalities, creating a larger space for AI Agents [3]. - Direct cost reduction and efficiency improvements are expected to increase customer willingness to pay for AI solutions [4]. Group 3: Advantages of Industry Leaders - Traditional industry leaders possess significant advantages due to their data capabilities, as only companies with a large customer base can gather sufficient high-quality data for model training [5]. - Leading companies are likely to become B-end AI super entry points due to their stronger product capabilities and broader functional coverage [5]. - Industry experience allows these companies to quickly identify potential scenarios and continuously update and release new products [5]. - The high investment threshold for developing large model AI applications (estimated at $500,000) further solidifies the advantages of leading companies [5]. Group 4: Market Potential and Future Outlook - The long-term market potential for management software combined with AI is estimated at 380 billion yuan, with the digitalization and intelligence integration expected to quadruple the industry size [7]. - The year 2025 is anticipated to mark the beginning of significant AI application deployment, with a focus on product value validation and technological catalysts in the upcoming quarters [7]. - By 2026, as AI applications mature, they are expected to open up a high-quality second growth curve for companies [7]. Group 5: Product Integration and Future Directions - AI is rapidly integrating into financial, human resources, marketing, and research fields, reshaping enterprise operations alongside existing management software [8]. - The future direction of AI applications includes enhancing front-end human-machine interactions and transforming enterprise operational models to improve overall efficiency [8].