Category: AWS Lambda

In this post, we explore a human-in-the-loop (HITL) framework in the form of architectural patterns teams can use to introduce agentic AI incrementally into eligibility workflows that are adapted to their programs, policies, and risk tolerances.

In this post, we describe how ITHAKA and Amazon Web Services (AWS) collaborated to build an on-demand PDF accessibility pipeline that remediates documents when users need them, serving researchers while using nonprofit resources responsibly. For organizations managing a large document collection under accessibility compliance deadlines, this post shows there is an affordable, practical path forward that doesn’t require converting an entire library upfront.

This post describes how Floy built an FM-based AI platform on AWS, from training and inference to clinical integration, that scales to meet the demands of modern radiology.

In this post, we review how AWS Lambda works today, introduce durable functions, walk through a document processing use case for child welfare, and explain when to choose durable functions over AWS Step Functions.

Amazon Web Services (AWS), through the Open Data on AWS and Amazon Sustainability Data Initiative (ASDI) programs, became a foundational collaborator from the outset, hosting Digital Earth Africa’s data on AWS infrastructure in Cape Town, South Africa, and enabling African users to access and analyze petabytes of satellite data at a speed and scale that would otherwise be out of reach.

In this post, we walk through the evidence pipeline, from Amazon Web Services (AWS) Config evaluations and AWS Security Hub findings through transformation and storage, to producing the dual-format output that satisfies FedRAMP 20x Phase 2 completeness requirements.

Today, AWS GovCloud (US) is the operational backbone of some of the nation’s most critical applications spanning security and defense, energy, public health and financial services. Fifteen years in, and that mission focus still defines everything AWS GovCloud (US) delivers.

In this post, you’ll learn how to build an identity incident review workflow that analyzes an event timeline, converts the findings into a strict incident record, and connects the review to a local account-control lookup. The examples separate observed facts from inferences and keep final incident and remediation decisions with a human reviewer.

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.