Build agent memory with NVIDIA NeMo Agent Toolkit and Amazon S3 Vectors
Amazon Web Services Venkata Sistla
NVIDIA NeMo Agent Toolkit (NAT) is shown being implemented with Amazon S3 Vectors as a custom persistent memory provider and deployed on Amazon EKS for an agent workflow. The example provisions an S3 Vectors index configured for 1024 dimensions to match Amazon Titan Text Embeddings V2. The result is a NAT memory subsystem that can automatically store and retrieve long-term agent memories via semantic vector search with metadata filtering, using the S3 Vectors backend.
Why it matters
Learn how to use Amazon S3 Vectors as the persistent memory layer within the NVIDIA NeMo Agent Toolkit (NAT), deployed on Amazon Elastic Kubernetes Service (Amazon EKS). This post shows how NAT's memory subsystem works and how to implement Amazon S3 Vectors as a custom memory provider, using a multi-agent investment research use case.