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Customer service teams face a persistent challenge. Existing chat-based assistants frustrate users with rigid responses, while direct large language model (LLM) implementations lack the structure needed for reliable business operations. When customers need help with order inquiries, cancellations, or status updates, traditional approaches either fail to understand natural language or can’t maintain context across multistep conversations.

This post explores how to build an intelligent conversational agent using Amazon Bedrock , LangGraph , and managed MLflow on Amazon SageMaker AI .…

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