用智能代理嵌套架构,让旧系统自动协作对话
Agentic Nesting: A New Methodology for Existing Enterprise Application Integration and Services
- 把旧系统变成可自主运行的AI代理,分层组织协同
- 支持自然语言跨系统查询与流程编排,无需改代码
- 适合有多个异构系统的大型企业做智能化整合
企业运营依赖多个异构业务系统和信息应用,导致数据孤岛和流程碎片化。尽管企业投入大量资源建设这些系统,但有效利用和协调仍面临巨大挑战。传统集成方法如企业服务总线(ESB)、API网关和机器人流程自动化(RPA)存在架构耦合高、运维成本上升、智能能力有限等固有缺陷。本文提出Agentic Nesting,一种多智能体协作框架,将现有企业应用封装为层级嵌套结构中的自主AI代理。不同于扁平连接,代理以分层治理拓扑组织,反映企业生态的组合复杂性。每个遗留系统被提取为数字代理代理,实现自然语言交互与自主操作;通过中央协调器分解任务并动态调度多个代理,提供统一对话接口,支持跨系统查询与流程编排。主要贡献包括提出‘应用即代理’集成范式和‘对话即集成’交互理念,并探索该方法在异构系统协同与大规模数据应用场景中的泛化潜力。
原文摘要 · Abstract (English)
Enterprise operations extensively rely on multiple heterogeneous business systems and information applications, which also result in severe data silos and process fragmentation. Enterprises have invested considerable financial and material resources in building these applications, however, effectively leveraging and orchestrating them remains a formidable challenge. Conventional approaches to enterprise application integration, encompassing middleware architectures such as Enterprise Service Bus (ESB), API gateway infrastructures, and Robotic Process Automation (RPA), suffer from inherent limitations like high architectural coupling, escalating operation and maintenance costs, and limited intelligence capabilities. This paper proposes Agentic Nesting, a multi-agent collaboration framework in which existing enterprise applications are encapsulated as autonomous AI agents within a hierarchically nested structure. Rather than flat interconnection, agents are organized into layered stewardship topologies that mirror the compositional complexity of enterprise ecosystems. The framework extracts a digital agent proxy from each legacy application to enable natural-language interaction and autonomous manipulation, coordinates multiple agents through a central orchestrator for task decomposition and dynamic dispatching, and exposes a unified conversational interface for cross-application querying and process orchestration. The main contributions of this paper are the proposition of the "Application-as-Agent" integration paradigm and the "Conversation-as-Integration" interaction philosophy, together with an exploration of the generalization potential of this methodology in scenarios encompassing heterogeneous system coordination, and large-scale data applications.
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