Market Surveillance Agent with LangGraph and Strands on AgentCore
Amazon/AWS
A multi-agent AI system for market surveillance is built using LangGraph for macro-orchestration and Strands for intelligent reasoning, deployed on AWS with Amazon Bedrock AgentCore. The architecture combines deterministic workflows with dynamic LLM-driven analysis, providing production-grade reliability and observability.
The post describes a multi-agent AI system for market surveillance that uses LangGraph for workflow orchestration and Strands for intelligent agent reasoning, deployed on AWS via Amazon Bedrock AgentCore. LangGraph manages state, directed graphs, checkpoint-based recovery, and human-in-the-loop interactions. Strands agents provide model-agnostic reasoning with tool integration and observability within individual workflow nodes. The system separates data discovery from retrieval to reduce hallucinations and injection attacks. LangGraph's graph-based state machines allow conditional branching and parallel execution, with persistent state management via checkpoints. Amazon Bedrock AgentCore provides managed runtime deployment, memory integration, and observability through CloudWatch and X-Ray. The complete solution is available on GitHub.
- Сокращения
- LLM = Large Language Model — Большая языковая модель
- SQL = Structured Query Language — Структурированный язык запросов
- MCP = Model Context Protocol — Протокол контекста модели
- SDK = Software Development Kit — Комплект разработчика
Source: AWS ML blog —
original
