Core Insights - The report by IDC evaluates the technical capabilities of leading Generative Business Intelligence (GenBI) vendors in China, highlighting the importance of AI-driven solutions in transforming traditional business intelligence [1] - Simat's Agent BI architecture and strong industry expertise have positioned it as a leader among eight evaluated vendors, achieving top scores in seven technical capability dimensions and full marks in financial and state-owned enterprise sectors [1][6] Group 1: Agent BI as a Technological Evolution - The report identifies Agent BI as the next direction for technology evolution, emphasizing the need for BI vendors to integrate Agent capabilities for improved data interaction and workflow [4] - The essence of this direction is the fusion of large language models (LLMs) with AI Agent capabilities, enabling complex problem understanding and multi-step reasoning [5] - Simat is recognized as a pioneer in applying AI Agent technology in the business intelligence sector, having launched various innovative features and platforms since 2019 [5][10] Group 2: Technical Capability Assessment - In the GenBI technical capability assessment, Simat scored first in seven dimensions, including data processing, data analysis, and model integration, showcasing a comprehensive technical system [6][7] - The integration of LLMs and AI Agents in Simat's Smartbi AIChat enhances analytical accuracy and depth, supporting complex data tasks and multi-source data integration [7] Group 3: Industry Application and Delivery - Simat has demonstrated exceptional capability in delivering solutions for complex industry scenarios, achieving full marks in the financial and state-owned enterprise sectors [8][9] - The report notes that Simat's Smartbi AIChat has been successfully implemented across various industries, improving development efficiency and business responsiveness [9] - Simat's experience in large-scale project delivery in finance and state-owned enterprises highlights its ability to meet the high demands of complex data environments [9][10]