AWS for Industries

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Surgical Intelligence Engine with AWS and NVIDIA — Edge-to-Cloud Technology for Med Techs

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.

Reimagining B-Pillar DFMEA: Why Ontology-Grounded AI Is the Future of Automotive Engineering

Reimagining B-Pillar DFMEA: Why Ontology-Grounded AI Is the Future of Automotive Engineering

This two-part series explores how ontology-grounded agentic AI transforms Design Failure Mode and Effects Analysis (DFMEA) for safety-critical automotive components — from the strategic imperative driving adoption to the architectural patterns and implementation details. In this post, we focus on: How AI can help with DFMEA, how engineering ontologies enable AI to reason for failure mechanisms rather than pattern-match, and what engineering leaders should prioritize today.

Flexible Telecom AI Workload Deployment Across AWS Hybrid Cloud

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

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.

Build an AI-powered 5G Signaling Trace Analyzer Using Amazon Bedrock

Build an AI-powered 5G Signaling Trace Analyzer Using Amazon Bedrock

Telecom engineers routinely analyze decoded signaling traces to troubleshoot network issues, validate procedure execution, and accelerate root cause analysis. In 5G networks, even a single registration attempt can span multiple layers such as NAS and NGAP. The registration attempt includes security context establishment and carries identifiers such as Subscription Concealed Identifier (SUCI), Globally Unique Temporary […]

Improving Defect Analysis and Quality Control with AI Diagnostics

How Jabil, Siemens Mendix, and AWS transformed manufacturing diagnostics in four weeks In manufacturing, every production defect means lost revenue, delayed shipments, and potential customer dissatisfaction. For Jabil, a global manufacturer with over 100 facilities across more than 25 countries serving customers in industries like data center infrastructure, healthcare, automotive, and energy, rapid defect diagnosis […]

Building a cloud-based EV charging monitoring platform with real-time AI analytics

Building a cloud-based EV charging monitoring platform with real-time AI analytics

In this post, we share how Iberdrola-BP Pulse in conjunction with GaleoTech, a systems integrator specialized in Internet of Things (IoT) for the energy sector, built EVBrain—a cloud-based platform on AWS that enables real-time monitoring, proactive incident detection, and AI-powered analytics for EV charging infrastructure across Spain.