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1. Building AI-ready data: Vanguard’s Virtual Analyst journey

   In this post, you'll learn how Vanguard built their Virtual Analyst solution by focusing on eight guiding principles of AI-ready data, the AWS services that powered their implementation, and the measurable business outcomes they achieved.

2. Run custom MCP proxies serverless on Amazon Bedrock AgentCore Runtime

   This post shows you how to deploy a serverless MCP proxy on Amazon Bedrock AgentCore Runtime that gives you a programmable layer to implement proper governance, controls, and observability aligned with an organization's security policies.

3. Migrating a text agent to a voice assistant with Amazon Nova 2 Sonic

   In this post, we explore what it takes to migrate a traditional text agent into a conversational voice assistant using Amazon Nova 2 Sonic. We compare text and voice agent requirements, highlight design priorities for different use cases, break down agent architecture, and address common concerns like tools and sub-agents for reuse and system prompt adaptation. This post helps you navigate the...

4. NVIDIA Nemotron 3 Nano Omni model now available on Amazon SageMaker JumpStart

   Today, we are excited to announce the day zero availability of NVIDIA Nemotron 3 Nano Omni on Amazon SageMaker JumpStart. In this post, we walk through the model architecture and key capabilities of Nemotron 3 Nano Omni, explore the enterprise use cases it unlocks, and show you how to deploy and run inference using Amazon SageMaker JumpStart.

5. Automate repetitive tasks with Amazon Quick Flows

   This post shows you how to build your first AI-powered workflow, using Amazon Quick, starting with a financial analysis tool and progressing to an advanced employee onboarding automation.

6. Build and deploy an automatic sync solution for Amazon Bedrock Knowledge Bases

   In this post, we explore an automated solution that detects S3 events and triggers ingestion jobs while respecting service quotas and providing comprehensive monitoring. This serverless solution uses an event-driven architecture to keep your knowledge base current without overwhelming the Amazon Bedrock APIs.

7. Build Strands Agents with SageMaker AI models and MLflow

   In this post, we demonstrate how to build AI agents using Strands Agents SDK with models deployed on SageMaker AI endpoints. You will learn how to deploy foundation models from SageMaker JumpStart, integrate them with Strands Agents, and establish production-grade observability using SageMaker Serverless MLflow for agent tracing. We also cover how to implement A/B testing across multiple model...

8. How Popsa used Amazon Nova to inspire customers with personalised title suggestions

   In this post, we share how we applied Amazon Bedrock and the Amazon Nova family of models to reimagine our Title Suggestion feature. By combining metadata, computer vision, and retrieval-augmented generative AI, we now automatically generate creative, brand-aligned titles and subtitles across 12 languages. Using the unified API of Amazon Bedrock, Anthropic’s Claude 3 Haiku, and Amazon Nova Lite...

9. Building Workforce AI Agents with Visier and Amazon Quick

   In this post, we show how connecting the Visier Workforce AI platform with Amazon Quick through Model Context Protocol (MCP) gives every knowledge worker a unified agentic workspace to ask questions in. Visier helps ground the workspace in live workforce data and the organizational context that surrounds it while letting your users act on the conversational results without switching tools.

10. Amazon Quick for marketing: From scattered data to strategic action

    Amazon Quick changes how you work. You can set it up in minutes and by the end of the day, you will wonder how you ever worked without it. Quick connects with your applications, tools, and data, creating a personal knowledge graph that learns your priorities, preferences, and network.