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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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…

Data modeling best practices for Amazon Quick Sight multi-dataset relationships
Today, we are excited to announce Multi-Dataset Relationships in Amazon Quick Sight. This new capability lets you define logical relationships between Quick Sig…

Enrich your datasets with business context: Migrating from legacy Topics to semantic datasets in Amazon Quick
In this post, we walk through what Dataset Enrichment is, how it differs from legacy Topics, and provide three migration scenarios with step-by-step guidance so…

A developer's guide to publishing agents in Gemini Enterprise and Google Cloud Marketplace
Software-as-a-service (SaaS) is evolving into Agents-as-a-service (AaaS). Instead of isolated applications, developers are creating AI agents that interoperate …

Report: 83% of organizations need to upgrade their infrastructure to support agentic AI
For years, enterprise AI has been synonymous with conversational AI — the customer service bots and digital assistants we interact with every day. But today, th…
20 questions for the Agentic Enterprise (and how Agent Platform can help)
If you’re an IT leader, you might be getting a lot of questions about how to build and deploy agents. The pressure to move fast is intense, but the engineering …

Drive proactive security, prioritize risks with Google Threat Intelligence and Wiz ASM
Being more proactive continues to be a leading goal for security organizations. As AI accelerates the pace of vulnerability discovery and exploitation, organiza…
The operating model advantage: Why AI winners are rewiring their organizations
The real AI advantage comes from redesigning how work is done and how decisions are made. Ultimately, success will depend on people and operating models support…
From the C-suite to the boardroom: Christiana Smith Shi on what it takes
For executives, the developmental opportunity may be clear, but what does board service really entail?…

Teaching models to forget: Selective unlearning with Amazon Nova
In this post, we introduce Reverse Direct Preference Optimization (rDPO), the novel unlearning technique behind Amazon Nova Customizable Content Moderation Sett…

From Hugging Face to Amazon SageMaker Studio in one click
Today, we’re excited to announce a deep-link integration between Hugging Face and Amazon SageMaker AI. Developers can now go from model discovery to hands-on ex…
Building America’s innovation engine: An interview with David Lebryk
The former US Treasury official shares how government can deliver in moments of crisis and how America’s public–private sector dynamic can help fuel its next er…