Category: Amazon Simple Queue Service (SQS)

This post is a follow-up to our March 2025 blog post, UTHealth Houston’s iDFax transforms medical fax management with Amazon Bedrock, which introduced the iDFax pilot and its early results.

This post shows how public sector and enterprise teams can build an agentic AI-powered classification system on Amazon Web Services (AWS) using the Strands Agents SDK, Amazon Bedrock, and serverless services. You will learn the architecture, the agent workflow, and how to implement this system using the Strands Agents SDK.

Real missions break perfect prototypes. Through Project MAVERICK (Mission Autonomy Versatile Rapid Innovation and Capabilities Kit), Amazon Web Services (AWS) confronts this reality head-on—bringing cloud capabilities directly into the field to test autonomous systems where it matters most.

Learn how student attentiveness and engagement analysis in live classrooms has been addressed with generative AI.

The Coupon Bureau (TCB) is modernizing how coupons work in the US with the first universal digital coupon standard: AI (8112). To make this possible, TCB needed to build a system that could support billions of coupon transactions in real time, integrate seamlessly with hundreds of providers and retailers, and deliver mission-critical reliability. By using AWS services, TCB designed a cloud-based architecture that processes high-volume events, delivers real-time webhook notifications, provides data recovery during outages, and scales seamlessly as adoption grows.

This post demonstrates how to build serverless workflows on AWS that process such data using AWS Step Functions and integrate with downstream systems that have concurrency limitations.

What if a Medicaid agency could make sure that their leadership and staff had access to a reliable, single source of truth for their data in one unified platform? The implementation of an operational data store (ODS) presents a viable solution. This post explains the architectural choices available with Amazon Web Services (AWS) to effectively create and maintain an ODS.

In this post, we discuss a solution that uses AWS services to improve government communication accessibility and meet federal accessibility requirements. The serverless architecture automates document-to-speech conversion and delivers information to citizens with visual disabilities.

Personalized therapy for diseases such as cancer utilizes an individual’s unique genomic profile to guide treatment decisions. However, the effect and clinical significance of most genetic variants are uncertain. Accurate classification of the clinical significance of novel genetic variants requires extensive curation of peer-reviewed biomedical literature. In recent years, generative AI has demonstrated promising results in information extraction and text summarization. In this post, we explore how various AWS-native solutions can be used to create a secure, retrieval-augmented, and cost-effective biomedical chatbot designed to facilitate biocuration.

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.