- AWS Solutions Library›
- Guidance for Multi-Agent Orchestration on AWS
Guidance for Multi-Agent Orchestration on AWS
Overview
This Guidance demonstrates how to address complex customer support challenges that require multi-step interactions and personalized responses by orchestrating specialized AI agents through proven coordination patterns on AWS. Modern customer service teams need sophisticated handling of diverse queries, from order management to technical troubleshooting, while maintaining conversation context across multiple interactions. The approach uses a Supervisor Agent that intelligently routes customer requests to specialized agents - each focused on specific domains like product recommendations, order tracking, or technical support - while ensuring secure authentication and real-time response streaming. You gain enterprise-grade reliability with built-in monitoring while maintaining complete control over agent behavior and seamless integration with both external systems and human agents.
How it works
Amazon Bedrock Multi-Agent Collaboration
This architecture showcases how a supervisor agent orchestrates multiple specialized sub-agents through Amazon Bedrock's native collaboration feature for comprehensive business scenarios. This pattern automatically handles task delegation and response aggregation across various functional agents with enterprise-grade reliability and built-in monitoring.
.68db1d801d8281605ece846494e188059033b369.png)
Agent Squad
This architecture diagram shows how specialized AI agents operate as independent microservices, each handling specific business domains through custom coordination logic. This pattern enables complete control over agent behavior and seamless integration with both external systems and human agents through message queues.
LangGraph
This architecture diagram shows a LangGraph-powered supervisor agent running on Amazon ECS that intelligently coordinates four specialized sub-agents through LangGraph’s agent orchestration framework, enabling seamless task delegation, context sharing, and response synthesis across distributed agents for comprehensive customer support scenarios.
Deploy with confidence
Ready to deploy? Review the sample code on GitHub for detailed deployment instructions to deploy as-is or customize to fit your needs.
Go to sample code:
Benefits
Deploy intelligent agent orchestration that routes queries to specialized agents automatically. Reduce tier-one support workload while delivering personalized responses across order management, product recommendations, and troubleshooting.
Enable continuous customer interactions with persistent memory across sessions and agent handoffs. Eliminate repetitive information gathering while providing personalized service based on customer history and preferences.
Leverage serverless agent architecture with Amazon Bedrock to handle varying customer demand automatically. Optimize costs with pay-per-use pricing while maintaining twenty-four seven availability for customer inquiries.
Disclaimer
The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.
References to third-party services or organizations in this Guidance do not imply an endorsement, sponsorship, or affiliation between Amazon or AWS and the third party. Guidance from AWS is a technical starting point, and you can customize your integration with third-party services when you deploy the architecture.
Did you find what you were looking for today?
Let us know so we can improve the quality of the content on our pages