Category: AWS Lambda

Learn how the Generative AI Innovation Center and Amazon Web Services (AWS), the NWS has developed a proof of concept (POC) to assist with extracting weather and geolocation information from text and images so it can verify the information against scientific data and give forecasters an early start as they document impacts.

Learn how the Boise State University Foundation transformed quarterly Microsoft Excel reports into real-time dashboards using Amazon Quick, a 780-fold improvement that fundamentally changed how leadership makes decisions. It extracts actionable insights from a decades-old legacy system while supporting a major comprehensive fundraising campaign.

In this post, we explain what the Progressing Snapshot program is, what the program is for, who it is for, and how Amazon Web Services (AWS) helps you lay the foundation to address many of the 40 snapshot controls.

Learn how the Login.gov team implemented a robust long-term log retention system that solved multiple architectural challenges while using Amazon Web Services (AWS) account-level subscription filters to provide capabilities that other approaches couldn’t match.

This post explains how to build exactly that using Strands Agents and Amazon Bedrock. The entire solution runs in about 200 lines of Python code, and you can have it working on your computer after completing the pre-requisite steps.

This post distills how one Amazon Web Services (AWS) customer in the defense and aerospace industry interpreted the U.S. International Traffic in Arms Regulations (ITAR) and concluded that U.S. commercial AWS Regions could support their export-controlled workloads, including AI workloads, when configured appropriately.

Learn how Amazon Web Services (AWS) operates inside a scoped compute environment with an AWS Identity and Access Management (IAM) execution role, network segmentation, and defense-in-depth security meeting FISMA, FedRAMP, and DoD CCSRG standards.

In this post, you’ll learn how KBR—a global science, technology, and engineering solutions organization—achieved a 33.5% cost savings and a 27.09% increase in pipeline processing speed by migrating geospatial processing workloads from an x86 Amazon Elastic Compute Cloud (Amazon EC2) M7i instance to AWS Graviton processors while maintaining data accuracy within 0.002% of x86 outputs.

Learn more about the Technology Readiness Experimentation (T-REX) 26-1 exercise at Camp Atterbury, Indiana, validated this approach in December 2025, demonstrating real-time monitoring, predictive analytics, and automated optimization across 20 technologies operating simultaneously.

In this post, we share how Scouting America used this AI assistant to transform youth enrollment.