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Automating competitive price intelligence with Amazon Nova Act
This post demonstrates how to build an automated competitive price intelligence system that streamlines manual workflows, supporting teams to make data-driven pricing decisions with real-time market insights.
Build reliable AI agents with Amazon Bedrock AgentCore Evaluations
In this post, we introduce Amazon Bedrock AgentCore Evaluations, a fully managed service for assessing AI agent performance across the development lifecycle. We walk through how the service measures agent accuracy across multiple quality dimensions. We explain the two evaluation approaches for development and production and share practical guidance for building agents you can deploy with confidence.
Build a FinOps agent using Amazon Bedrock AgentCore
In this post, you learn how to build a FinOps agent usingnbsp;Amazon Bedrock AgentCore that helps your finance team manage AWS costs across multiple accounts. This conversational agent consolidates data fromnbsp;AWS Cost Explorer,nbsp;AWS Budgets, andnbsp;AWS Compute Optimizernbsp;into a single interface, so your team can ask questions like "What are my top cost drivers this month?" and receive immediate answers.
Building an AI powered system for compliance evidence collection
In this post, we show you how to build a similar system for your organization. You will learn the architecture decisions, implementation details, and deployment process that can help you automate your own compliance workflows.
Accelerating software delivery with agentic QA automation using Amazon Nova Act
In this post, we demonstrate how to implement agentic QA automation through QA Studio, a reference solution built with Amazon Nova Act. You will see how to define tests in natural language that adapt automatically to UI changes, explore the serverless architecture that executes tests reliably at scale, and get step-by-step deployment guidance for your AWS environment.
AWS launches frontier agents for security testing and cloud operations
I'm excited to announce that AWS Security Agent on-demand penetration testing and AWS DevOps Agent are now generally available, representing a new class of AI capabilities we announced at re:Invent called frontier agents. These autonomous systems work independently to achieve goals, scale massively to tackle concurrent tasks, and run persistently for hours or days without constant human oversight. Together, these agents are changing the way we secure and operate software. In preview, customers and partners report that AWS Security Agent compresses penetration testing timelines from weeks to hours and the AWS DevOps Agent supports 3–5x faster incident resolution.
Can your governance keep pace with your AI ambitions? AI risk intelligence in the agentic era
Traditional frameworks designed for static deployments cannot address the dynamic interactions that define agentic workloads. AI Risk Intelligence (AIRI), from AWS Generative AI Innovation Center, provides the automated rigor required to govern agents at enterprise scale—a fundamental reimagining of how security, operations, and governance work together systemically.
There are more AI health tools than ever—but how well do they work?
Earlier this month, Microsoft launched Copilot Health, a new space within its Copilot app where users will be able to connect their medical records and ask specific questions about their health. A couple of days earlier, Amazon had announced that Health AI, an LLM-based tool previously restricted to members of its One Medical service, would…
How Ring scales global customer support with Amazon Bedrock Knowledge Bases
In this post, you'll learn how Ring implemented metadata-driven filtering for Region-specific content, separated content management into ingestion, evaluation and promotion workflows, and achieved cost savings while scaling up.
Reimagine marketing at Volkswagen Group with generative AI
In this post, we explore the challenges that Volkswagen Group faced in producing brand-compliant marketing assets at scale. We walk through how we built a generative AI solution that generates photorealistic vehicle images, validates technical accuracy at the component level, and helps enforce brand guideline compliance alignment across the ten brands.
Build a solar flare detection system on SageMaker AI LSTM networks and ESA STIX data
In this post, we show you how to use Amazon SageMaker AI to build and deploy a deep learning model for detecting solar flares using data from the European Space Agency's STIX instrument.
Deliver hyper-personalized viewer experiences with an agentic AI movie assistant using Amazon Bedrock AgentCore and Amazon Nova Sonic 2.0
In this post, we walk through two use cases that help enhance the user viewing experience using agentic AI tools and frameworks including Strands Agents SDK, Amazon Bedrock AgentCore, and Amazon Nova Sonic 2.0. This agentic AI system uses a Model Context Protocol (MCP) to deliver a personal entertainment concierge that understands user preferences through natural dialogue.
Run Generative AI inference with Amazon Bedrock in Asia Pacific (New Zealand)
Today, we’re excited to announce that Amazon Bedrock is now available in the Asia Pacific (New Zealand) Region (ap-southeast-6). Customers in New Zealand can now access Anthropic Claude models (Claude Opus 4.5, Opus 4.6, Sonnet 4.5, Sonnet 4.6, and Haiku 4.5) and Amazon (Nova 2 Lite) models directly in the Auckland Region with cross region inference. In this post, we explore how cross-Region inference works from the New Zealand Region, the models available through geographic and global routing, and how to get started with your first API call. We
Building age-responsive, context-aware AI with Amazon Bedrock Guardrails
In this post, we walk you through how to implement a fully automated, context-aware AI solution using a serverless architecture on AWS. This solution helps organizations looking to deploy responsible AI systems, align with compliance requirements for vulnerable populations, and help maintain appropriate and trustworthy AI responses across diverse user groups without compromising performance or governance.
Accelerating LLM fine-tuning with unstructured data using SageMaker Unified Studio and S3
Last year, AWS announced an integration between Amazon SageMaker Unified Studio and Amazon S3 general purpose buckets. This integration makes it straightforward for teams to use unstructured data stored in Amazon Simple Storage Service (Amazon S3) for machine learning (ML) and data analytics use cases. In this post, we show how to integrate S3 general purpose buckets with Amazon SageMaker Catalog to fine-tune Llama 3.2 11B Vision Instruct for visual question answering (VQA) using Amazon SageMaker Unified Studio.
Introducing Amazon Polly Bidirectional Streaming: Real-time speech synthesis for conversational AI
Today, we’re excited to announce the new Bidirectional Streaming API for Amazon Polly, enabling streamlined real-time text-to-speech (TTS) synthesis where you can start sending text and receiving audio simultaneously. This new API is built for conversational AI applications that generate text or audio incrementally, like responses from large language models (LLMs), where users must begin synthesizing audio before the full text is available.
Unlocking video insights at scale with Amazon Bedrock multimodal models
In this post, we explore how the multimodal foundation models (FMs) of Amazon Bedrock enable scalable video understanding through three distinct architectural approaches. Each approach is designed for different use cases and cost-performance trade-offs.
Deploy voice agents with Pipecat and Amazon Bedrock AgentCore Runtime – Part 1
In this series of posts, you will learn how streaming architectures help address these challenges using Pipecat voice agents on Amazon Bedrock AgentCore Runtime. In Part 1, you will learn how to deploy Pipecat voice agents on AgentCore Runtime using different network transport approaches including WebSockets, WebRTC and telephony integration, with practical deployment guidance and code samples.
Reinforcement fine-tuning on Amazon Bedrock with OpenAI-Compatible APIs: a technical walkthrough
In this post, we walk through the end-to-end workflow of using RFT on Amazon Bedrock with OpenAI-compatible APIs: from setting up authentication, to deploying a Lambda-based reward function, to kicking off a training job and running on-demand inference on your fine-tuned model.
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