Category: Technical How-to

This post explores how AI agents powered by Strands Agents on AWS can transform geospatial workflows, making spatial data accessible to any government worker through natural language interactions.

As a large Amazon Web Services (AWS) public sector customer, you might need information about which accounts contributed to this month’s billing surge, which workloads generated the most security findings, or which services experienced the highest adoption rates. Although straightforward in single-account environments, finding such information becomes complex when organizations manage hundreds or thousands of AWS accounts.

Now you can save time and instill confidence in documents more quickly by using Amazon Quick Automate, which creates a set of agents to complete complex business tasks with reasoning. Amazon Quick Automate is a powerful multi-agent automation capability within Amazon Quick Suite that streamlines complex enterprise processes spanning multiple departments, systems, and applications. Read this post to learn more.

This post explores how prompt engineering—the art of effectively communicating with AI—can help educators guide their students in building powerful educational tools using PartyRock.

In this blog post, we demonstrate how public sector organizations can overcome the challenges that emerge when integrating Amazon Redshift and other AWS relational databases with Amazon Bedrock. You’ll learn how to utilize enterprise data to generate AI-powered analytical insights by using natural language queries through Amazon Bedrock Agents and Amazon Bedrock Knowledge Bases. This custom solution enables seamless connectivity between your structured data sources and generative AI applications, eliminating the need for data duplication and significantly reducing development effort.

Whether you’re a technical architect, systems integrator, or government technology leader, this post provides the technical insights needed to understand and implement MOSIP (Modular Open-Source Identity Platform) on AWS effectively.

This blog post provides a comprehensive overview of the custom large language model (LLM) development lifecycle for public sector use, emphasizing scientific methodology and measurable outcomes.

Trusted Research Environments (TREs) provide secure access to sensitive data, enabling research while controlling data movement to meet governance requirements. In this post, we review core TRE concepts, examine TRE history and related initiatives, and explore key considerations for successfully deploying a TRE on AWS.

This post shares lessons learned by Pariveda, a strategy and technology services firm, during the implementation of a scalable and flexible data integration pipeline for a customer. We review three approaches, all leveraging AWS Glue and Salesforce capabilities, to securely publish data to polymorphic objects and compounded fields.

Public sector organizations and technology vendors across industries—from healthcare and education to public safety and citizen services—struggle with complex identity integration requirements when deploying applications across multiple facilities and jurisdictions. This post demonstrates how organizations can eliminate integration delays using an automated metadata extraction solution built on AWS that provides self-service access to Amazon Cognito user pools metadata through a serverless REST API.