Langchain

Building agentic AI applications on a modern data mesh strategy on AWS requires fine-grained access control enforced at every layer of the data interaction chain. The proposed architecture extends the original with three key changes: replacing Amazon OpenSearch Serverless with Amazon S3 Vectors, replacing general-purpose Amazon S3 with Amazon S3 Tables governed by AWS Lake Formation, and exposing the data mesh as Model Context Protocol (MCP) tools through AgentCore Gateway with AWS Lambda-backed interceptors. This approach provides a secure, scalable data foundation for production agentic AI, reducing vector storage and query costs by up to 90% and increasing transactions per second by up to 10 times. The practical implication for engineers building AI systems is the ability to enforce fine-grained access control and provide a governed data mesh for agentic AI applications.