Category: Amazon Bedrock

Reducing unplanned downtime in automotive paint shops requires unifying siloed operational data into a contextualized fabric that enables AI-driven root cause analysis and anomaly detection. Today, when a paint shop line goes down, the industrial engineer must manually correlate data across Supervisory Control and Data Acquisition (SCADA) systems, Manufacturing Execution Systems (MES) platforms, downtime logs, […]

This post was co-written with Harsh Vardhan, Global Head of the Digital Innovation Hub, from Apollo Tyres Ltd. Every recipe change on a tyre extrusion line triggers a stabilization period—minutes of off-spec material that must be reworked or scrapped. For high-mix manufacturers running 30–35 setup changes per day, this adds up to 5–6% of total […]

This is part 3 of our three-part series on how Amazon Web Services (AWS) aligns with MPA Content Security Best Practices with a particular focus on media archives.

This guide walks one agent through all six pillars: a Parts Inventory Agent for an automotive manufacturing plant.

In this post, we demonstrate how a large North American Utility is currently running a multi-agent AI architecture on Amazon Bedrock AgentCore to compress alarm triage from hours to minutes, avoiding the manual, multi-system investigation that operators perform dozens of times per shift. We will walk through the industry problem, the multi-agent design, and a reference implementation on GitHub that you can deploy into your own environment.

As part of its ongoing commitment to operational excellence, Mary Kay sought to further accelerate the investigation and resolution of routine infrastructure events through AI-powered automation and intelligent orchestration by activating a capability most Amazon Web Services (AWS) Enterprise Support customers already pay for but never use: the AWS DevOps Agent.

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.

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 […]