Building an Enterprise-Grade Multi-Agent Customer Service System with LangGraph

This article discusses the challenges of single-agent architectures in e-commerce customer service and presents a multi-agent system design using LangGraph to address issues like task decomposition, tool execution, data retrieval, and governance.

Details

The article discusses the limitations of single-agent architectures in e-commerce customer service, where user requests often contain multiple intents and require coordinated access to different data sources. The proposed system follows a layered architecture with an application layer for user-facing services, a feature layer for core business capabilities, a technical layer for standardized frameworks and interfaces, and a platform layer for infrastructure and data management. The application layer includes services for user management, session handling, and knowledge base indexing. The feature layer hosts the multi-agent system, which handles intent routing, task decomposition, tool execution, and result aggregation. It also has safety guardrails, hybrid knowledge retrieval, offline/online indexing, and natural language to Cypher debugging. The technical layer provides core capabilities like agent scheduling, retrieval augmentation, and workflow orchestration using LangChain and LangGraph. The interface layer uses Vue, FastAPI, and Open API. The platform layer has a dual-model strategy with an online DeepSeek model and a self-hosted vLLM model, along with a hybrid data storage solution and cloud infrastructure.