Group 1 - The report titled "2025 Intelligent Analysis Agent White Paper" discusses the significant role of intelligent analysis agents in driving scientific decision-making within enterprises, emphasizing their importance in data value extraction and decision efficiency enhancement amid the explosion of data and digital transformation [1][2][8] - Intelligent analysis agents utilize Agentic AI to create a closed-loop system of "perception - reasoning - planning - execution - evolution," enabling a shift from data visualization to decision automation [1][9] - The technology behind intelligent analysis agents includes natural language interaction, multi-task processing, and continuous learning, with various technical modules working together to accomplish complex analytical tasks [1][2][9] Group 2 - SwiftAgent is highlighted as a representative product, featuring low barriers to data access, intelligent attribution analysis, AI report generation, and multi-end adaptation, widely applied in decision-making, management, and operational scenarios [2][31] - The competitive landscape for intelligent analysis agents is intense, with notable performances from tech companies in the US and China, including major players like Salesforce and Microsoft, as well as emerging companies like Shushi Technology [2][41][46] - The report indicates that intelligent analysis agents are transforming enterprise decision-making paradigms, urging companies to embrace this technology to enhance data-driven decision-making capabilities and achieve sustainable development [2][41] Group 3 - The report outlines the evolution of AI agents, categorizing them into various types, including creative agents, employee agents, code agents, security agents, customer service agents, and intelligent analysis agents, each serving unique functions within the enterprise ecosystem [24][25] - Intelligent analysis agents focus on data processing and analysis, serving as critical tools for enterprises to extract value from vast amounts of data, with platforms like Tableau Pulse and Power BI Copilot providing advanced data visualization and insights [31][32] - The emergence of LLM (Large Language Model) agents signifies a new phase in intelligent analysis, enabling proactive insights, deep semantic understanding, and automated decision-making processes [33][39] Group 4 - The report emphasizes the importance of integrating intelligent analysis agents into enterprise operations, highlighting their ability to provide real-time insights and enhance decision-making efficiency [39][40] - The industry landscape for intelligent analysis agents is characterized by a mix of established tech giants and innovative newcomers, with significant advancements in AI-driven data analysis products [41][44][46] - The report also notes the role of open-source projects in the intelligent analysis agent space, fostering collaboration and innovation among developers globally [48]

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编辑部 整理自 凹非寺 量子位 | 公众号 QbitAI 当大模型改变人类信息交互方式、算力成本不断降低，一个关键问题浮现在每一位企业决策者面前： 如何让AI真正成为企业的"智慧大脑"，驱动业务决策全面升级？ 大模型来了，万物皆可Chat， 但企业级AI应用的规范复杂得多 ，不是简单的Excel+Chat就能完成。 在第三届AIGC产业峰会上，数势科技联合创始人谭李，指出了当下行业面临的挑战。 而AI Agent的出现为这一难题提供了解决性方案 。 数势科技就是代表之一，他们通过SwiftAgent平台，为企业打造随时在线的" 数据分析与决策平台"，让每一位业务人员都能像与专业分析师 对话一样，轻松获取数据洞见，做出更明智的业务决策。 为了完整体现谭李的思考，在不改变原意的基础上，量子位对演讲内容进行了编辑整理，希望能给你带来更多启发。 中国AIGC产业峰会是由量子位主办的AI领域前沿峰会，20余位产业代表与会讨论。线下参会观众超千人，线上直播观众320万+，累计曝光 2000万+。 话题要点 以下是演讲全文： 供需侧都在迎来新范式 感谢主持人，各位来宾，大家上午好！ 我是数势科技的谭李，今天非常荣幸和大家做 ...