AWS Public Sector Blog

Category: Public Sector

Modernizing border control with digital arrival cards on AWS Cloud

Modernizing border control with digital arrival cards on AWS Cloud

Learn how Somapa Information Technology PCL (SomapaIT), an AWS Partner, chooses Amazon Web Services (AWS) Cloud to implement DAC systems because of its global footprint, security, high availability, and scalability.

How NWS forecasters use generative AI for innovative storm reporting

How NWS forecasters use generative AI for innovative storm reporting

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.

How the University of São Paulo is transforming how researchers access greenhouse gas data for the Amazon rainforest with AWS

How the University of São Paulo is transforming how researchers access greenhouse gas data for the Amazon rainforest with AWS

Learn how researchers in the University of São Paulo Research Center in Greenhouse Gas Innovation (RCGI) greenhouse gas (GHG) program saw an opportunity to develop a system that enabled close monitoring of the forest using data systems and data spaces in the cloud. They created Digital Amazon, a distributed data space network with open access that integrates CO2 and greenhouse gas emissions data collected by the university with other data sources to support critical and timely climate action and intervention in the Amazon Forest.

How NTU FRESH is using AWS to build predictive food safety at scale

How NTU FRESH is using AWS to build predictive food safety at scale

In this post, we walk you through how FRESH is translating cloud-enabled analytics into practical tools that support resilient, trusted food systems, starting with a deep dive into dynamic shelf-life modeling. Specifically, we detail how AWS services such as Amazon Simple Storage Service (Amazon S3), AWS Glue, and Amazon SageMaker AI are used to build and train predictive models.

How healthcare organizations are advancing innovation while meeting digital sovereignty requirements with AWS

How healthcare organizations are advancing innovation while meeting digital sovereignty requirements with AWS

Healthcare is entering a new era. Advances in AI, data analytics, and cloud computing are creating opportunities ranging from accelerating drug discovery and enabling precision medicine to helping clinicians detect disease earlier and spend more time with patients. As healthcare organizations embrace these technologies, they face an equally important responsibility: safeguarding some of the world’s […]

Campaign reporting transformation at Boise State University Foundation

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.

How AWS and a local community organization built a developer engagement model that works

How AWS and a local community organization built a developer engagement model that works

Learn how between Amazon Web Services (AWS) and HUMANBULB, the community organization behind the AWS Sacramento User Group — became a model that other cloud companies and community leaders can replicate. In this post, we share what we built, what we learned, and how other AWS teams and community leaders can apply the same approach in their own cities.

Turning vague agent personality goals into versioned prompts with Amazon Bedrock

Turning vague agent personality goals into versioned prompts with Amazon Bedrock

The methodology described in this post translates subjective personality requirements into testable behaviors, versioned prompts, and documented boundaries. It addresses several dimensions of Responsible AI at AWS, an eight-dimension framework that guides how we build and evaluate AI systems.