Core Insights - The report highlights a shift in the financial research landscape from "universal models" to a "matrix of specialized agents" empowered by AI, which aims to reduce time-consuming and repetitive tasks traditionally reliant on analysts' complex skills [2] - AI tools like AlphaEngine can quickly construct DCF models and provide target price ranges for companies, significantly enhancing decision-making support [2][14] - Compared to general AI models like DeepSeek, AlphaEngine and Alpha agents focus on deep optimization for vertical research scenarios, emphasizing task automation and industry chain integration [2] - The integration of AI in asset allocation is expected to yield sustainable excess returns, necessitating the combination of AI outputs with human expert qualitative judgments [2] AlphaEngine Application Cases - AlphaEngine can efficiently assist in financial valuation modeling by processing extensive data and generating structured outputs, including target price ranges based on various scenarios [14][21] - The tool's ability to reference reliable research reports enhances the credibility of its outputs, effectively mitigating the "AI hallucination" issue [14][23] Alpha派 Application Cases - Alpha派 serves as an intelligent investment research app that can generate performance reviews for specific companies, allowing users to customize the analysis style and focus points [66] - The platform's ability to provide structured outputs and reference relevant reports aids in data verification and reduces the risk of misinformation [69] Comparison of AlphaEngine and Alpha派 - AlphaEngine is characterized by its detailed and foundational approach, providing comprehensive background and framework comparisons, making it suitable for in-depth research [93] - Alpha派 is designed for efficiency and clarity, offering concise insights and actionable strategies, making it ideal for decision-makers needing quick access to core viewpoints [93]