Category: Amazon Simple Storage Service (S3)

Amazon Web Services (AWS) customers building software-defined ground segment solutions with the AWS Ground Station now have more confidence in their solution: they can integrate their DevOps practices with AWS Ground Station’s digital twin feature, which became generally available in August. The digital twin is useful for both aspiring and existing AWS Ground Station customers to achieve faster outcomes without applying for satellite licensing and more cost-effectively than scheduling a production satellite contact. Read this post to learn more.

This post explores the architectural design and security concepts employed by Radboud University Medical Center Nijmegen (Radboudumc) to build a secure artificial intelligence (AI) runtime environment on Amazon Web Services (AWS). Business leaders dealing with sensitive or regulated data will find this post invaluable because it demonstrates a proven approach to using the power of AI while maintaining strict data privacy and security standards.

In the age of generative artificial intelligence (AI), data isn’t just king—it’s the entire kingdom. Our previous blog post, Anduril unleashes the power of RAG with enterprise search chatbot Alfred on AWS, highlighted how Anduril Industries revolutionized enterprise search with Alfred, their innovative chat-based assistant powered by Retrieval-Augmented Generation (RAG) architecture. In this post, we examine the technical intricacies that make this system possible.

Data Review & Transfer Component (DRTC) on Amazon Web Services (AWS) provides a seamless solution to review, approve, and automate sensitive data transfer requests into and out of secure enclaves. In this post, we take you through the benefits of using DRTC to review data and other research artifacts for sensitivity prior to transfer into and out of these secure environments, in particular Trusted Research Environments (TREs).

In an earlier post, Build secure and scalable data platforms for the European Health Data Space (EHDS) with AWS, we discussed a reference architecture for building secure and scalable data platforms for secondary usage of health data in alignment with the European Health Data Space (EHDS) using Amazon Web Services (AWS). This follow-up post walks you through the technical implementation details for building such federated data governance and analysis platforms using AWS. Whether you are a healthcare organization, technology provider, or systems integrator, this post aims to equip you with the technical knowledge to build a secure data platform for secondary usage of health data in alignment with the EHDS Regulation.

Sharing data is essential for organizations to make informed decisions and foster innovation. Amazon Web Services (AWS) offers a variety of tools and services to help distribute data securely and at scale. Whether it’s sharing public data for the common good, monetizing private datasets for business purposes, or collaborating with colleagues, AWS provides the necessary infrastructure and support. Read this post to learn more.

Government agencies handle vast volumes of bureaucratic documents daily, ranging from tax forms to medical records. This document-heavy workflow, often reliant on manual processing, can result in delays, errors, and increased operational inefficiencies, causing frustration among both employees and stakeholders. This post explores how intelligent document processing (IDP) solutions from Amazon Web Services (AWS) can modernize bureaucratic workflows, improve efficiency, and enhance service delivery within government agencies.

AWS App Studio is a low-code development platform for users to build, deploy, and manage applications without extensive coding knowledge. It is designed to streamline the application development process, making it more accessible to a wider range of users, including business users, IT professionals, and startups that don’t have large specialized IT teams. This post guides you through the process of creating a user-friendly create, read, update, and delete (CRUD) application to efficiently manage birth certificate applications using AWS App Studio.

Today, generative artificial intelligence (AI) is at the core of many of the decisions and technologies businesses across the globe are implementing. The linchpin to ensuring that generative AI is effective depends on the foundation models (FMs) storing the data. To make sure that those FMs are pulling the correct data, Amazon Web Services (AWS) has developed a solution through Amazon Bedrock to generate SQL to answer user questions about the data. The solution was developed to support the Federal Institute of São Paulo (IFSP) and has optimized their decision-making.

In this post, we explore how generative artificial intelligence (AI), powered by services such as Amazon Bedrock and Amazon SageMaker, can be harnessed to meet the unique challenges of AWS GovCloud (US). We highlight use cases that demonstrate the potential of generative AI to enhance efficiency, automate workflows, and extract insights—all within a secure, compliant framework.