AWS for Industries

This blog post will detail how Genmab, a leading biotech company, built an automated pipeline on AWS that handles whole-slide images from start to finish, cutting analysis time from hours to under 30 minutes per batch and reducing manual work by 80 percent. We will walk through how Genmab achieved this using AWS services and share the key lessons they learned along the way.

This blog post covers the concepts of network tracing and how it can be implemented across a complex, distributed environment where different teams run applications in separate AWS accounts, using Amazon Virtual Private Cloud (VPC) feature called Amazon VPC Traffic Mirroring.

Learn more about the MyWingstop platform, built on Amazon Web Services (AWS), designed specifically to perform flawlessly during the year’s biggest sports moments, from championship games to tournament weekends.

In this post, we show how EHR companies, healthcare independent software vendors (ISVs), and tech-enabled provider organizations can use Amazon Connect Health to embed these capabilities into their existing workflows using a single, unified Software Development Kit (SDK).

In this blog we explore how Liftoff built and scaled Cortex, their AI-powered growth platform, on AWS using the latest neural network technology and AWS Graviton Processors. We discuss how Cortex addresses the challenges of training hundreds of models per day, with over 1 Petabyte of new data daily. All, while lowering infrastructure costs and improving customer performances.

Learn more about Kiro — an agentic AI-powered IDE built by AWS that helps you go from prototype to production with spec-driven development — and how to improve Kiro’s bioinformatics workflow abilities, we built the AWS HealthOmics Kiro Power — a companion package that automatically configures the HealthOmics Model Context Protocol (MCP) server and provides Kiro with domain-specific steering guides.

This blog will cover how PQD enables the transformation of after-sales vehicle quality from a reactive to a proactive, data-driven approach enabled by connected vehicle data, software-defined architectures, and AI/ML services from AWS.

Amazon Devices engineers needed AI assistance directly in their design tools to accelerate hardware development. But AI agents running locally on engineering workstations had no way to authenticate with AWS services without distributing credentials, creating unacceptable security risks. The Design Technologies team solved this challenge by implementing browser-based authentication that establishes user identity and enables […]

In this blog post, we’ll explain why BMW Group chose Amazon Web Services, Inc. (“AWS”) as its cloud provider to deliver this user experience and dive deep into how the team solved the technical challenges along the way.

In this post, we’ll unpack what ChatGPT Apps are, why they’ve become a strategic priority for retailers, and how they fit into a broader agentic commerce vision. We’ll also show you why AWS is the ideal back-end infrastructure.