Category: Intermediate (200)

Learn how Thermo Fisher Scientific built an AI-powered patient-matching platform on AWS, modernizing its clinical trial recruitment data foundation and using AWS Countdown Premium to de-risk the production launch.

Building multimodal AI/ML pipelines on Amazon EC2 means scaling distributed compute, controlling costs across stages, and keeping up with new models and hardware. This post shows how the Ray-powered Anyscale application on AWS helps you deploy Ray across three compute options and scale from prototype to production without code changes.

Accelerating API adoption while reducing operational overhead is a challenge that every growing organization faces. For Revinate, a hospitality provider serving over 12,500 hotels worldwide and powering more than 1.25 billion guest profiles, Amazon API Gateway became the foundation of their solution. Revinate empowers hoteliers to connect directly with guests at every touchpoint, driving $24 […]

Smarsh used the AWS Well-Architected Framework’s Agentic AI Lens to review its first agentic workload. Because the lens is not yet selectable in the console, the team encoded it as a Claude skill that assessed all 150 best practices against the workload’s GitHub repository and produced an evidence-backed review workbook in hours instead of days.

Attach governance context such as classification, retention, residency, and PII flags directly to your Amazon S3 objects with S3 annotations. This post walks through the end-to-end pattern and the handful of S3 behaviors that decide whether your governance design is correct.

The next generation of AWS Resilience Hub introduces recommended resilience testing: four pre-configured, AWS FIS-powered tests that validate how your service detects and recovers from failures across Availability Zones, dependencies, and Regions, turning your resilience policy into evidence-backed pass or fail results.

Learn how to combine deterministic orchestration with bounded agentic reasoning using AWS Step Functions and the Amazon Bedrock AgentCore harness. This medical coding workflow escalates cheapest-first: a safety block-list, then exact matching, then an AI agent only for terms that need judgment, keeping every routing decision auditable.

Dynata reimagined its development lifecycle with AI, moving from AI-assisted coding to the AI-Driven Development Lifecycle (AI-DLC) methodology with Kiro IDE. Learn how the company reduced the development phase of full-stack features from three to four sprints to roughly one, with every team aligned from the start.

The next generation of AWS Resilience Hub adds three capabilities to keep workload scope and resilience requirements aligned with your running environment: Amazon EKS label support for service input sources, generative AI-powered Dependency Insights, and resilience policy sharing through AWS Organizations.

This post presents a reference architecture that turns public sequencing data into plain-language answers about antimicrobial resistance (AMR) genes. It pairs AWS HealthOmics for managed genomics processing with a grounded Amazon Bedrock AgentCore agent, so researchers can ask questions without writing bioinformatics code or SQL.