Category: Messaging

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.

This post demonstrates on Massive Multitask Language Understanding (MMLU) [Hendrycks et al., 2021], an open-source multiple-choice benchmark accessible via Hugging Face Hub, selecting four business-relevant subjects.

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

In this blog, learn how Kite, a Gilead Company, modernized its bioinformatics infrastructure by transitioning from fragmented, project-specific workflows to a standardized, cloud-enabled approach using AWS HealthOmics. Discover how this collaboration with AWS Professional Services enabled over 100 researchers to access scalable, self-service computational workflows through their existing laboratory systems—without requiring CLI or infrastructure expertise.

Learn how at the 2026 AWS Life Sciences Symposium, we brought together some of the most innovative companies in MedTech to share what it takes to build in this environment, and what becomes possible when you have the right data foundation and AI backbone.

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.

Learn how the Energy HPC Orchestrator (EHO) on AWS represents a new paradigm, built on components that work together to create a flexible, scalable processing environment.

This blog post will detail how Genmab, a leading biotech company, built an automated pipeline on AWS that handles whole-slide images from start to finish, cutting analysis time from hours to under 30 minutes per batch and reducing manual work by 80 percent. We will walk through how Genmab achieved this using AWS services and share the key lessons they learned along the way.

In this post, we show how EHR companies, healthcare independent software vendors (ISVs), and tech-enabled provider organizations can use Amazon Connect Health to embed these capabilities into their existing workflows using a single, unified Software Development Kit (SDK).

Learn how to transform collections operations for banks and fintechs with AI and ML on AWS The Business Challenge Financial institutions face mounting pressure in collections operations. Traditional debt collection operates on a simple playbook: aggressive phone calls, generic messaging, and rule-based workflows. Yet customers have unique capacity to pay (income, assets, competing obligations), willingness […]