Original article excerpt
Server-side extracted preview paragraphs from the original source.
In this post, you will learn patterns for implementing production-ready multi-tenant systems using Amazon Bedrock AgentCore. You will see these patterns demonstrated through healthcare AI agents that serve multiple clinics and hospitals.
Building multi-tenant AI applications presents new architectural challenges. You need complete tenant isolation between customers, different service tiers with different capabilities, granular cost tracking, and observability per tenant. Without these, you could risk exposing customer data, not providing appropriate quality of service to your customers or running up unforeseen costs.
In this post, you will learn patterns for implementing production-ready multi-tenant systems using Amazon Bedrock AgentCore. You will see these patterns demonstrated through healthcare AI agents that serve multiple clinics and hospitals. While the post uses healthcare as the example domain, the architectural patterns and implementation techniques apply broadly to various multi-tenant AI applications. Whether you’re building SaaS platforms, enterprise solutions serving multiple business units, or managed services for different customer organizations, you can use these architectural patterns to build your solution.
This blog post is part 2 of the series, Building multi-tenant agents with Amazon Bedrock AgentCore. Part 1 explores design considerations for architecting multi-tenant agentic applications and the framework needed to address SaaS architecture challenges with Amazon Bedrock AgentCore.
GitHub repo for the sample code: https://github.com/aws-samples/sample-agentcore-and-multitenancy-blog
This solution demonstrates how to use native capabilities of Amazon Bedrock AgentCore to achieve complete tenant isolation using AWS-managed services. The architecture implements a three-level hierarchy: Tier → Tenant → User, where you enforce isolation at every layer through documents in knowledge base, memory, model access, and cost tracking. A tiering strategy is a common pattern in SaaS applications where tenants are grouped into distinct service tiers based on their needs – such as Basic and Premium, usage patterns, or pricing plans. Each tier defines a set of features and quality of service available to tenants within that group. This approach allows SaaS providers to serve a diverse customer base with differentiated experiences while maintaining operational efficiency.
To see how this works in practice, the example solution implements two service tiers for tier-based differentiation: