AWS for Industries

In this post, we introduce a fully serverless pattern that solves this problem using AWS AppSync Events, Amazon Nova Sonic, and Amazon Bedrock AgentCore.

In this post, you’ll learn how financial institutions can use Amazon Bedrock AgentCore and Strands Agents SDK — an open source framework for building intelligent, model-driven AI agents — to automate their complaint management process through a near real-time agentic solution that classifies complaints with defensible rationale, captures evidence at each decision point, tracks SLA compliance, assigns clear remediation ownership, and improves mean time to resolution.

Manufacturing organizations can now reduce simulation cycle times from days to hours by integrating Teamcenter Simulation with AWS ParallelCluster — eliminating high performance compute (HPC) queuing bottlenecks while maintaining full data traceability. The demand for high-fidelity engineering simulations such as Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and Multi-physics analyses continues to grow as […]

This post is a technical deep dive. It explains the Sandbox’s multi-tenant isolation model along with its inherited security and cost controls. It then examines two production-grade multi-agent AIOps systems our teams built on top of it, including the LangGraph (an open source multi-agent orchestration framework) state model, Retrieval-Augmented Generation (RAG) design, OpenSearch query patterns, parallel root cause analysis (RCA) with self-falsification, and the human-in-the-loop safeguards that help make agentic recovery safe in production. Code samples are illustrative and simplified for readability.

In this post, we build on that foundation by constructing specialized AI agents for each data modality along with a supervisor agent that orchestrates cross-modal analysis using Amazon Bedrock AgentCore and Strands Agents SDK. We also train predictive AI models with Amazon SageMaker AI to predict patient outcomes from multimodal features. To further explore the implementation details and get hands-on experience, refer to the accompanying code repository.

In this two-part blog series, we show how you can build agents that interact with multimodal HCLS data, making it easier for end users to query, explore, and ask questions of the data. We build on previous guidance for multimodal data analysis, which demonstrates how to store, query, and analyze clinical, genomic, and medical imaging data using purpose-built AWS services.

Introduction Voice communications infrastructure remains a critical challenge for organizations migrating to the cloud. While IT workloads successfully move to AWS, Session Border Controllers (SBCs) often stay anchored to legacy hardware platforms that cannot scale dynamically or integrate with modern cloud operations. Ribbon’s SBC Cloud Native edition (CNe) on Amazon Elastic Kubernetes Service (Amazon EKS) […]

Learn more about Engineering Development Hub (EDH), a unified, cloud-based engineering workbench that brings together the applications, compute, and data you need to design, test, and validate complex systems—all in a single, open source environment.

In a previous blog post, we described how AUMOVIO built an AI-powered engineering assistant on Amazon Bedrock that generates automotive-grade embedded code. That system accelerates development

When AWS released Amazon S3 Tables, this calculus changed. In this post, you will learn how Amica reduced their ETL job runtimes by 80% by building a data lake for core insurance data using S3 Tables.