AWS for Industries

This blog post introduces a serverless dynamic pricing platform built on Amazon Web Services (AWS) that helps restaurants automatically adjust menu prices based on real-time demand patterns. The solution enables restaurants to maximize revenue during peak hours while attracting price-sensitive customers during slower periods.

Across R&D organizations, AI agents are beginning to design molecules, plan syntheses, execute assays, and analyze experimental data. But these systems often operate without awareness of prior experiments, failed approaches, or parallel work happening across the organization. In this blog, learn how Sanofi recognized this limitation early and partnered with Amazon Web Services (AWS) to reimagine the foundation for AI-enabled discovery.

In the retail and consumer packaged goods (CPG) industry, accurate food labeling is a critical safety requirement. Retailers face an increasingly complex challenge: manually verifying that thousands of packaged foods comply with FDA regulations—particularly the allergen labeling requirements under the Food Allergen Labeling and Consumer Protection Act (FALCPA) of 2004.

Novo Nordisk, a leading global healthcare company, and Amazon Web Services (AWS) today announced a strategic partnership to accelerate drug discovery and modernize operations through AI and cloud technologies.

Manufacturers operating multi-plant environments struggle with a common challenge: production data trapped in isolated systems across facilities, preventing teams from detecting anomalies early or responding to disruptions before they cascade. In this post, you will learn how to build a Manufacturing Control Tower on AWS that unifies plant-floor data streams, applies Agentic AI for autonomous […]

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.