The AWS Machine Learning Blog presents a guide to architecting and deploying a production-ready multi-agent AI system, using a market surveillance scenario as the example. The setup combines LangGraph for workflow orchestration and Strands for agent reasoning, running on Amazon Bedrock AgentCore.
The post covers state-driven orchestration, checkpoint-based recovery, and the use of AgentCore memory and observability capabilities.
Why it matters
The example illustrates how multiple components can be combined into a production-oriented agent system, including recovery and observability features relevant to deploying such workflows.
Who should care
Developers and teams working with multi-agent systems on Amazon Bedrock, as well as those interested in market surveillance use cases, may find the architecture and deployment walkthrough relevant.