AWS for Industries

Category: Amazon Bedrock

How WellRithms achieved 30 times faster bill processing with AWS

How WellRithms achieved 30 times faster bill processing with AWS

WellRithms achieved 30 times faster bill processing by combining AWS services with its deep medical billing expertise. This blog post explores how the company transformed document preparation from a manual constraint into a scalable, AI-powered capability, and the results they achieved.

Trust-Earned Autonomy: How Texas Capital Bank demonstrates an AI agent that commits to the core banking ledger, then reverses itself

Trust-Earned Autonomy: How Texas Capital Bank demonstrates an AI agent that commits to the core banking ledger, then reverses itself

Texas Capital Bank is a full-service financial services firm headquartered in Dallas, Texas, serving commercial, consumer, and institutional clients. Its technology organization builds internal platforms across several areas, including document intelligence for lending. Processing a commercial loan package is slow, manual work: an analyst reads a 200-plus-page package and extracts financial obligations, servicing requirements, and covenant terms by hand, a task that can take hours per package and is easy to get wrong.

Reduce SMT Defects with Agentic AI: Automating Polarity Validation on AWS

Surface Mount Technology (SMT) polarity programming defines how a polarity-sensitive component feeds from tape reel or tray to the pick-and-place machine, designed to help maintain correct orientation on the Printed Circuit Board Assembly (PCBA). Get it right, and boards run clean. Get it wrong by 180°, and downstream systems (Automated Optical Inspection (AOI), X-ray, In-Circuit […]

How Morningstar built a financial advisor AI assistant powered by Amazon Bedrock AgentCore

In this blog, learn how Morningstar designed the agentic orchestration, enforced guardrails, enabled comprehensive audit trails for a regulated environment, and deployed a production system that keeps the advisor in control while automating the research-to-action workflow.

Building AI-augmented B-pillar DFMEA on AWS: Architecture, multi-agent orchestration, and implementation

Building AI-augmented B-pillar DFMEA on AWS: Architecture, multi-agent orchestration, and implementation

In this post, we deliver the implementation blueprint. We walk through the complete reference architecture built on Amazon Web Services (AWS), break down the layer service topology, detail the multi-agent orchestration pattern using Amazon Bedrock AgentCore and the Strands Agents SDK.

Introducing seven new features of the Agentic Shopping Assistant on AWS

Introducing seven new features of the Agentic Shopping Assistant on AWS

Earlier this year, we announced the Agentic Shopping Assistant on AWS, a generative AI-powered solution that helps retailers give online shoppers the kind of expert guidance they would get from a knowledgeable in-store associate. The Agentic Shopping Assistant on AWS brings the expertise and insights behind Amazon’s successful Alexa for Shopping AI assistant to retail customers.

From Days to Minutes: How we built Multi-Agent KYC/KYB on AWS

From Days to Minutes: How we built Multi-Agent KYC/KYB on AWS

This post documents a working system. Five KYC/KYB checks, each with its own agent architecture, prompt methodology, and failure modes. We built it, ran it, broke it, fixed it, and are publishing the full method so you can build your own.

Reducing paint shop downtime with Industrial Data Fabric on AWS

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, […]

How Apollo Tyres Uses AI-Driven APC for First Time Right Tyre Extrusion

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 […]