Build Advanced Customer Support LLM Multi-Agent Workflow

Socure developed a multi-agent generative AI support framework to help its small customer support team manage growing volumes of technical, product, compliance, and account-related inquiries for an identity verification platform handling sensitive PII and transaction data. Built with LangGraph and AWS Bedrock, the system routes queries from Slack or a support portal through contextual rephrasing and intent classification, then runs up to three specialized agents in parallel across domains including API documentation, internal knowledge, business intelligence, Salesforce data, transaction troubleshooting, and legal compliance. An evaluation component selects the strongest proposed response using relevance, accuracy, clarity, confidence, and citations, while low-confidence cases are escalated to human representatives. The design incorporates chat history, account context, feedback collection, response logging, and human oversight to support quality control and model refinement in a regulated setting. In an internal beta, Socure reports automating more than half of routine support tickets, reducing response times for common questions by 70%, improving satisfaction scores, and increasing team capacity without additional headcount. Future work includes multi-step reasoning approaches such as ReWOO and ReAct to address more complex investigations requiring planning, tool use, and coordinated agent workflows.

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