Category: AWS Lambda

In this blog, learn more about the availability of Amazon Bedrock AgentCore in the AWS GovCloud (US-West) Region, giving government and regulated industries a fully managed solution to build, deploy, and operate AI agents at production scale, without needing to manage the underlying infrastructure. This launch is part of Amazon’s broader commitment to invest more than $50 billion in cloud and AI infrastructure, giving government customers access to the same cutting-edge AI capabilities available in commercial Regions.

In Part 2 of our two-part series, we discuss the architecture of the Signal-Activated Agent Pattern and its application for proactive government AI. For Part 1, see Signal-activated generative AI: How agencies can reach more people and react faster.

This two-part series introduces the Signal-Activated Agent Pattern—an architectural approach, backed by a deployable Amazon Web Services (AWS) reference implementation, that helps government AI platforms move from generic, reactive question-answering to proactive, contextually personalized decision support. With this solution, agencies can reach more people, respond faster, and deliver the right value to the right official at each decision point.

This post explores how an agentic AI architecture on Amazon Web Services (AWS) modernizes the procurement lifecycle from solicitation to proposal evaluation while maintaining compliance with government regulations including United States of America FAR (Federal Acquisition Regulation),United States of America DFARS (Defense Federal Acquisition Regulation), and Canadian procurement frameworks (Public Service Procurement Canada (PSPC) /Shared Services Canada (SSC).

This post presents two complementary patterns for implementing per-user token guardrails on Amazon Bedrock from Amazon Web Services (AWS).

Every major agent framework has a security model for this. Amazon Web Services (AWS), Microsoft, and Google each ship agent solutions with authentication and credential management built in. Amazon Bedrock Agents, for example, enforces AWS Identity and Access Management (IAM)-based authorization on which AWS Lambda functions, Amazon Simple Storage Service (Amazon S3) buckets, and Amazon Bedrock Knowledge Bases an agent might invoke.

This post shows how public sector and enterprise teams can build an agentic AI-powered classification system on Amazon Web Services (AWS) using the Strands Agents SDK, Amazon Bedrock, and serverless services. You will learn the architecture, the agent workflow, and how to implement this system using the Strands Agents SDK.

Learn how Amazon Web Services (AWS) offers a fundamentally different approach. By deploying agentic AI—specialized AI agents that work collaboratively to analyze, validate, and route documentation—federal agencies can dramatically accelerate conformity processing while maintaining or improving quality and compliance standards.

In this blog, learn how NASA’s Earth Science Data and Information System (ESDIS) is migrating over 170 petabytes of Earth science data to AWS to provide equitable access to researchers worldwide, eliminating the “data fortress” problem while achieving significant cost efficiencies through intelligent tiering, serverless architecture, and economies of scale. The post also details how NASA made over 6,000 Earth Science collections visible in the Registry of Open Data on AWS, enabling seamless discovery and analysis for the broader AWS user community.

Learn how the GDAC supports over 35 agencies, turning siloed information into the cross-agency insights Georgia’s policymakers need to better serve constituents.