AWS for Industries
Category: Artificial Intelligence
Deploy diagnostic-quality imaging globally with MedDream and AWS HealthImaging
Learn how by combining MedDream’s FDA-cleared diagnostic viewer with AWS HealthImaging and automated AWS Cloud Development Kit (AWS CDK) deployment, you can deploy a complete, production-ready medical imaging solution in under an hour—achieving sub-second loading times and reducing storage costs by up to 40% compared to on-premises infrastructure.
Coins in Motion: Building agentic blockchain payments for in-vehicle experiences
Agentic blockchain-based payments are poised to transform in-vehicle driving experiences. As vehicles become increasingly connected and autonomous, they are evolving from passive transportation tools into active economic agents capable of conducting their own financial transactions [see HBR Article, 2021]. Imagine your car automatically paying for highway tolls, electric charging sessions, parking fees, or even purchasing […]
Reduce P&ID analysis time by 80% with hybrid AI maintenance planning
Every major industrial facility relies on thousands of highly complex technical drawings called Piping and Instrumentation Diagrams (P&IDs) that serve as the DNA of industrial operations. These diagrams show how equipment connects, materials flow, and safety systems protect workers and assets. These diagrams are complex. For example, where 511 industrial P&ID documents may mean 1,397,710 […]
Deploying industrial AI on AWS: Building the autonomous factory
Manufacturers have been using AI and robotics in their operations for years. The question is no longer how these technologies improve operations, it’s how to deploy industrial AI autonomously at production scale without replacing existing infrastructure, locking into a single vendor, or spending years in pilot mode. AWS provides the digital thread foundation, edge-to-cloud infrastructure, […]
Edge-to-Cloud Architecture for Real-Time Surgical Intelligence with AWS and NVIDIA
Learn how to architect an end-to-end pipeline that processes surgical video at the edge for de-identification, instrument detection, and surgical phase recognition—while using the cloud for model training and fleet management.
How Multi-Agent AI Turns Supply Chain Data into Decisions and Actions
This blog explains how multi-agent AI systems can automate the reasoning chain between supply chain data and action—closing the gap that control towers leave open by translating natural language questions into SQL queries, performing root cause analysis, and generating execution-ready materials in seconds rather than hours.
Deploy Agentic Bidding Without Sacrificing Speed: ARTF Containers with NVIDIA GPU Acceleration on AWS
AWS is building the infrastructure for programmatic advertising’s shift to agentic AI where autonomous agents plan campaigns, orchestrate models, and optimize bids across the full funnel. Today, the bidstream processes billions of decisions daily, each within milliseconds, relying on rule-based heuristics and lightweight models constrained by real-time latency budgets and CPU-only infrastructure. That constraint is […]
Flexible Telecom AI Workload Deployment Across AWS Hybrid Cloud
This blog introduces a structured placement approach for AI workloads across AWS hybrid infrastructure. By evaluating each AI lifecycle phase against four dimensions (data sovereignty, latency, data gravity, and operational readiness), architects can determine the optimal deployment tier among AWS Regions, AWS Local Zones, AWS Outposts and AWS AI Factories.
Building a HIPAA-ready generative AI architecture for healthcare on AWS
In this post, we describe a comprehensive, HIPAA-ready generative AI architecture for healthcare on Amazon Web Services (AWS) using a defense-in-depth approach. By layering compliance controls at multiple distinct levels, this architecture creates a system where no single point of failure compromises patient data protection, and each component that touches ePHI is independently auditable.
Highlights from the 2026 AWS Life Sciences Symposium: MedTech Track
Learn how at the 2026 AWS Life Sciences Symposium, we brought together some of the most innovative companies in MedTech to share what it takes to build in this environment, and what becomes possible when you have the right data foundation and AI backbone.








