每经AI快讯，有投资者在投资者互动平台提问：AI智能体最近一系列政策出台后，对公司有何影响？ （记者 王晓波） 彩讯股份（300634.SZ）10月15日在投资者互动平台表示，近期有关AI智能体领域的一系列政策出台， 进一步明确了行业发展的方向与规范，为公司相关业务带来了更为有利的发展环境。彩讯股份自2023年 起便前瞻性地布局AI智能体领域，依托完全自主研发的Rich AIBox智能体平台—集成了多模态交互与行 业知识图谱的企业级AI应用一站式解决方案，持续推进业务落地。该平台支持低代码快速开发，深度 融合了知识存储与检索、AI治理、多智能体协同等关键能力，已形成企业知识库、智能客服、智能营 销、AI BI四大核心产品线。我们能够基于企业的真实业务场景，端到端地整合深度研究及AI工具调用 等核心功能，为企业量身打磨专属智能体，有效降低AI应用的落地门槛。目前，公司已成功推出包括 客服智能体、语音智能体、企业大脑、数字员工、智能邮箱在内的多款AI应用，并在电信、能源、金 融、交通、政务等多个行业实现了头部客户的业务落地。这些进展为公司把握政策机遇、拓展市场奠定 了坚实基础。 未来，公司将积极顺应政策导向，持续 ...

Core Insights - The core issue for enterprises regarding AI is its practical application and ability to solve real problems, rather than just being a concept or demonstration [1][3] - The rise of "intelligent agents" in 2025 is driven by business needs for tools that can effectively address challenges [3][4] Group 1: Intelligent Agents Development - The Intelligent Agent Development Platform 3.0 enhances features such as RAG (Retrieval-Augmented Generation), multi-agent collaboration, long-term memory, and plugin ecosystems, allowing agents to work continuously across tasks and scenarios [3][4] - Intelligent agents can now remember user interactions and follow up on needs, moving beyond one-time responses [3][4] Group 2: Real-World Applications - Intelligent agents are being applied in various sectors, such as hotel services where they can interpret guest requests and manage room conditions, and in industrial quality inspection where they identify product defects in real-time [4][5] - The media industry benefits from intelligent agents that streamline the entire content production process, enhancing efficiency [4] Group 3: Open Source and Industry Trends - Tencent's Youtu-Agent framework has been open-sourced, gaining over 2700 stars on GitHub, positioning it as a leading project in the intelligent agent domain [6] - The company emphasizes the importance of combining technology with real industry scenarios, as frameworks without genuine data and context may lack substance [6] Group 4: Future Directions - The focus is on addressing current pain points in the industry rather than rushing to define "super intelligent agents," with an emphasis on improving reliability and reducing erroneous outputs [7] - The industry is still in an exploratory phase, and overcoming obstacles is essential for the widespread adoption of intelligent agents as effective productivity tools [7]