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1. Simulate realistic users to evaluate multi-turn AI agents in Strands Evals

   In this post, we explore how ActorSimulator in Strands Evaluations SDK addresses the challenge with structured user simulation that integrates into your evaluation pipeline.

2. Scaling seismic foundation models on AWS: Distributed training with Amazon SageMaker HyperPod and expanding context windows

   This post describes how TGS achieved near-linear scaling for distributed training and expanded context windows for their Vision Transformer-based SFM using Amazon SageMaker HyperPod. This joint solution cut training time from 6 months to just 5 days while enabling analysis of seismic volumes larger than previously possible.

3. Control which domains your AI agents can access

   In this post, we show you how to configure AWS Network Firewall to restrict AgentCore resources to an allowlist of approved internet domains. This post focuses on domain-level filtering using SNI inspection — the first layer of a defense-in-depth approach.

4. Rocket Close transforms mortgage document processing with Amazon Bedrock and Amazon Textract

   Through a strategic partnership with the AWS Generative AI Innovation Center (GenAIIC), Rocket Close developed an intelligent document processing solution that has significantly reduced processing time, making the process 15 times faster. The solution, which uses Amazon Textract for OCR processing and Amazon Bedrock for foundation models (FMs), achieves a strong 90% overall accuracy in document...

5. Persist session state with filesystem configuration and execute shell commands

   In this post, we go through how to use managed session storage to persist your agent's filesystem state and how to execute shell commands directly in your agent's environment.

6. 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.

7. 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...

8. Build a FinOps agent using Amazon Bedrock AgentCore

   In this post, you learn how to build a FinOps agent using Amazon Bedrock AgentCore that helps your finance team manage AWS costs across multiple accounts. This conversational agent consolidates data from AWS Cost Explorer, AWS Budgets, and AWS Compute Optimizer into a single interface, so your team can ask questions like "What are my top cost drivers this month?" and...

9. 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.

10. 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.