Practice
How AI actually ships: enterprise case studies, engineering lessons from production, adoption data and ROI evidence.
How AI actually ships: enterprise case studies, engineering lessons from production, adoption data and ROI evidence.
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Disaggregated prefill and decode for LLM inference on SageMaker HyperPod
In this post, we show how to implement DPD with vLLM on Amazon SageMaker HyperPod using the HyperPod Inference Operator.…

How KTern.AI built agentic AI for SAP on Amazon Bedrock AgentCore
Evolving from a traditional software as a service (SaaS) platform into a next-generation agentic AI platform meant orchestrating multiple specialized agents acr…

Deploying quantized models on Amazon SageMaker AI with Unsloth
In this post, you will learn four deployment patterns for taking models that have already been quantized with Unsloth and deploying them on AWS infrastructure. …

Scaling agentic workflows with native case management in Amazon Quick Automate
In this post, we show you how to combine case management with agentic automation capabilities in Quick Automate. We introduce case management and explore the li…

Build a semantic layer for agentic AI on AWS with Stardog and Amazon Bedrock AgentCore
In this post we show how to build a semantic layer on AWS using Stardog’s Semantic AI Application over Amazon Aurora and Amazon Redshift, and how to run a Stran…

Real-time dental image verification with Amazon SageMaker AI at Henry Schein One
This post describes how Henry Schein One closed that gap by building Image Verify, an AI-powered quality verification system on Amazon SageMaker AI that evaluat…
AI in five industries: What’s now, and what’s next
The headlines are everywhere. The nuance is more elusive. In these video Explainers, McKinsey partners go sector by sector to parse what’s happening with AI now…
Author Talks: In Hollywood and in business, it’s cool to be kind
In Lead with Kindness, television writer and producer Melinda Hsu explores how so-called soft skills like empathy, mindfulness, and collaboration can result in …
The real AI advantage
The next wave of value from AI will flow to those leaders who redesign business models, eliminate friction, and build organizations that learn faster than the c…

Enhancing enterprise inference on Amazon SageMaker HyperPod with data capture, Hugging Face, NVMe, and Route 53 integration
In this post, we walk through five capabilities now available in SageMaker HyperPod inference: multi-tier data capture for auditing and model improvement, direc…

MCP tool design: Practical approaches and tradeoffs
In this post, we show where MCP tool design goes wrong and how to fix it with practical context engineering approaches.…

Solve harder problems with AlphaEvolve, now available to everyone on Google Cloud
Many of the most challenging and valuable problems in the world are related to optimization. Now, AI is now making these problems tractable. If you've ever trie…
Agents, robots, and us: How AI reshapes work and skills in Latin America
Most skills will still be needed—but how people use them will change as they work alongside intelligent machines.…

Introducing Claude apps gateway for AWS
Today, we're announcing the Claude apps gateway for AWS, a self-hosted control plane that gives organizations a single point of control over access, cost, and p…

Building and connecting a production-ready ecommerce MCP server using Amazon Bedrock AgentCore and Mistral AI Studio
In this post, you build and connect that server end to end. You will implement MCP tools, set up two-layer JSON Web Token (JWT) authentication, deploy with AWS …

Automatically sort and prioritize your mailboxes by using Amazon Bedrock
In this post, we show how organizations in the public sector can automate their email management using a generative AI solution powered by Amazon Bedrock.…

Powering scientific discovery: BYOKG and GraphRAG for intelligent pharmaceutical research
In this post, we explore how Graph-based Retrieval Augmented Generation (GraphRAG) is transforming scientific research by combining graph databases with generat…

Manage AI applications on Mac with Jamf’s AI Governance and Amazon Bedrock
In this post, we show how you can use Jamf’s AI Governance with Amazon Bedrock to configure, deploy, and validate managed settings for AI applications across a …

Securing Amazon Bedrock AgentCore Runtime with AWS WAF
This post shows you two architecture patterns that address this problem. Both use an internet-facing ALB with AWS WAF and route traffic through a VPC Interface …
From adoption to impact: Three horizons of AI transformation
Most organizations are still early in their AI journeys. A new global survey reveals how companies can progress from individual adoption to enterprise-wide valu…
Cost versus value: Managing agentic AI system performance
Per-token pricing has stopped being a useful measure for what enterprises actually pay for gen AI. A conversation with David Tepper, CEO of Pay-i, delves into t…
From healthcare to health: Asia’s longevity opportunity
On average, people are living longer than before, raising a broader conversation about how to create an ecosystem that effectively combines the delivery of care…
Reimagining logistics pricing
Logistics players can focus on four pricing strategies in the AI era.…

How AWS Finance teams reclaimed hundreds of hours with Amazon Quick
In this post, we show how AWS Finance used chat agents and Flows in Amazin Quick to transform two of their most time-consuming workflows.…

Build an AI-powered AWS support companion with Amazon Bedrock AgentCore
In this post, you build an AWS Support Companion using Amazon Bedrock AgentCore. The agent uses Strands Agents as the orchestration framework and connects to AW…

Monitoring discriminative ML models using Amazon SageMaker AI with MLflow
Implementing a data and model monitoring solution is necessary to maintain prediction accuracy and help achieve the best outcome for your machine learning use c…

Build a serverless image editing agent with Amazon Bedrock AgentCore harness
This post walks through building a serverless image editor where users upload a photo, describe an edit in plain English, and receive the result in seconds. The…

Build a unified semantic layer across datasets with multi-dataset Topics in Amazon Quick
In this post, we walk through how multi-dataset Topics work, explain how the chat agent uses defined relationships to generate cross-dataset queries, and demons…

Multi-dataset Topic best practices for Amazon Quick Chat
This post is for data architects, business intelligence (BI) engineers, and analytics engineers building or optimizing Quick Sight Topics for natural-language C…

Data modeling patterns for Amazon Quick Sight multi-dataset relationships
In this post, we shift from concepts to patterns. For each schema, you’ll find a table structure, use cases, implementation steps, and sample SQL queries. We al…