Tag: Amazon S3

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).

PointHealth AI, a healthcare technology (HealthTech) startup, and Protege, a data innovator specializing in artificial intelligence (AI)-ready datasets, are working with Amazon Web Services (AWS) to combine de-identified demographic and clinical information from millions of patient records, in order to deliver more precise and informed treatment recommendations. This data-informed strategy aims to give doctors the information they need to prescribe the right care for a patient’s unique needs—on the first try.

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.

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.

In this post, we explore how AWS services, open source software, and bespoke source code can help address resource sharing enhancements requested by public sector customers using AWS Outposts. This solution aims to provide greater flexibility, control, and cost management for organizations leveraging Outposts in multi-account environments, specifically focusing on key AWS resources, including Amazon Elastic Compute Cloud (Amazon EC2), Amazon Elastic Block Store (Amazon EBS), and Amazon Simple Storage Service (Amazon S3) on Outposts.

This post discusses how FIA Tech, a leading technology provider for the exchange traded derivatives (ETD) industry, built the Trade Data Network (TDN) on Amazon Web Services (AWS). TDN is an industry initiative that provides a shared ledger of trading information to address the fragmentation and lack of transparency in ETD post-trade processing. The TDN initiative currently includes 17 banks/brokers and 40 investment managers and hedge funds with combined assets under management of more than $34 trillion.