Build agent memory with NVIDIA NeMo Agent Toolkit and Amazon S3 Vectors
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.
AWS Machine Learning highlights the importance of memory engineering for production multi-agent systems, emphasizing Amazon S3 Vectors as a solution that meets the necessary architectural requirements. The article then delves into the implementation of Amazon S3 Vectors as the persistent memory layer within NVIDIA NeMo Agent Toolkit (NAT), which is deployed on Amazon Elastic Kubernetes Service (Amazon EKS) for operational control.
By the end of the post, readers will understand the workings of NAT's memory subsystem and how to implement Amazon S3 Vectors as a custom memory provider, using a multi-agent investment research use case as an example.
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