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  • Building Supercharger: How Rocket Close optimized title operations with agentic AI

    calendar Jun 12, 2026 · aws.amazon.com/blogs/machine-learning
    Building Supercharger: How Rocket Close optimized title operations with agentic AI

    In this post, we explore how Rocket Close built a solution using Strands Agents, large language models (LLMs), Amazon Bedrock, Amazon Bedrock Knowledge Bases, and Model Context Protocol (MCP) tools. We cover solution features, the rationale for the technology stack, lessons learned, and the business impact at Rocket …


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  • Build a meeting prep and follow-up assistant with Amazon Quick and Cisco Webex MCP servers

    calendar Jun 12, 2026 · aws.amazon.com/blogs/machine-learning
    Build a meeting prep and follow-up assistant with Amazon Quick and Cisco Webex MCP servers

    This post shows how to build a custom meeting prep and follow-up assistant using Amazon Quick and Cisco Webex MCP servers. From a single prompt, the agent finds an upcoming Webex meeting, reviews prior meeting summaries and transcripts, and pulls related Vidcast highlights and transcript context. It then searches Webex …


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  • From PDFs to insights: Architecting an intelligent document processing pipeline with AWS generative AI services

    calendar Jun 12, 2026 · aws.amazon.com/blogs/machine-learning
    From PDFs to insights: Architecting an intelligent document processing pipeline with AWS generative AI services

    This post outlines the development of a cost-effective and scalable intelligent document processing pipeline on AWS, powered by Amazon Bedrock and its features. BDA is a managed service within Amazon Bedrock that automates the extraction of insights from documents. We demonstrate how BDA extracts and analyzes document …


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  • Built from the inside out: How AWS Professional Services became a frontier team first

    calendar Jun 12, 2026 · aws.amazon.com/blogs/machine-learning
    Built from the inside out: How AWS Professional Services became a frontier team first

    AWS Professional Services (AWS ProServe) compressed engagement timelines from months to days, not by adding artificial intelligence (AI) tools to an existing process, but by fundamentally rebuilding how we deliver from the inside out. In this post, we share how AWS ProServe became a frontier team, the practices that …


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  • Extract Data with On-demand and Batch Pipelines Dynamically

    calendar Jun 11, 2026 · aws.amazon.com/blogs/machine-learning
    Extract Data with On-demand and Batch Pipelines Dynamically

    This post demonstrates an intelligent document processing pipeline that consists of both on-demand inference and batch inference options on Amazon Bedrock to enable the flexibility on the document processing time and cost. Link to article: …


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  • Evaluate AI agents systematically with Agent-EvalKit

    calendar Jun 11, 2026 · aws.amazon.com/blogs/machine-learning
    Evaluate AI agents systematically with Agent-EvalKit

    Agent-EvalKit is an open-source toolkit (Apache 2.0) that makes this evaluation infrastructure available by integrating with AI coding assistants, including Claude Code, Kiro CLI, and Kilo Code. This post walks through how Agent-EvalKit works across its six evaluation phases, using a travel research agent built with …


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  • Spot trends faster, sort smarter: Unlocking Sparklines and Custom Sort in Amazon Quick

    calendar Jun 11, 2026 · aws.amazon.com/blogs/machine-learning
    Spot trends faster, sort smarter: Unlocking Sparklines and Custom Sort in Amazon Quick

    Today, we’re excited to announce two new capabilities that make Quick Sight dashboards even more expressive and business-aligned: sparklines and custom sort for controls. In this post, we walk through both features, what they are, when to use them, and how to configure them, with real-world scenarios that bring them …


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  • Optimize blueprint extraction accuracy in Amazon Bedrock Data Automation

    calendar Jun 11, 2026 · aws.amazon.com/blogs/machine-learning
    Optimize blueprint extraction accuracy in Amazon Bedrock Data Automation

    Blueprint instruction optimization is a BDA feature that automatically refines your extraction instructions to address this challenge directly. You provide three to ten example documents with expected values, and BDA refines your blueprint instructions to improve accuracy in minutes, not weeks. No separate model …


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  • How frontier teams are reinventing AI-native development

    calendar Jun 11, 2026 · aws.amazon.com/blogs/machine-learning
    How frontier teams are reinventing AI-native development

    Frontier teams are not just using AI to code faster. They’re redesigning how software gets built. The result is 4.5x productivity gains, in some cases more than 10x. Link to article: https://aws.amazon.com/blogs/machine-learning/how-frontier-teams-are-reinventing-ai-native-development/


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  • Stop hand-tuning kernels: How Neuron Agentic Development accelerates AWS Trainium optimizations

    calendar Jun 10, 2026 · aws.amazon.com/blogs/machine-learning
    Stop hand-tuning kernels: How Neuron Agentic Development accelerates AWS Trainium optimizations

    Today, we’re announcing the Neuron Agentic Development capabilities: a collection of AI agents and skills that make this possible for developers building on AWS Trainium and AWS Inferentia. In this post, we explain how the Neuron Agentic Development capabilities accelerate the kernel development workflow. Link to …


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  • Build an AI-Powered Equipment Repair Assistant Using Amazon Bedrock AgentCore

    calendar Jun 10, 2026 · aws.amazon.com/blogs/machine-learning
    Build an AI-Powered Equipment Repair Assistant Using Amazon Bedrock AgentCore

    In this post, you build an AI-powered equipment repair assistant using Amazon Bedrock AgentCore that helps farmers and field technicians diagnose equipment problems, identify required parts, and access manufacturer-approved repair procedures through natural language. The solution uses AgentCore Runtime with the Strands …


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  • Scale Robot Reinforcement Learning with NVIDIA Isaac Lab on Amazon SageMaker AI

    calendar Jun 9, 2026 · aws.amazon.com/blogs/machine-learning
    Scale Robot Reinforcement Learning with NVIDIA Isaac Lab on Amazon SageMaker AI

    In this post, we show how to train robot policies for the Unitree H1 humanoid with NVIDIA Isaac Lab on Amazon SageMaker AI across two compute options: Amazon SageMaker HyperPod and Amazon SageMaker Training Jobs. Link to article: …


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  • Hands-free first notice of loss: Using Strands Agents and Amazon Bedrock AgentCore Browser Tool for intelligent claims intake

    calendar Jun 9, 2026 · aws.amazon.com/blogs/machine-learning
    Hands-free first notice of loss: Using Strands Agents and Amazon Bedrock AgentCore Browser Tool for intelligent claims intake

    In this post, we demonstrate how a hands-free FNOL intake system combines agents built with the Strands Agents SDK for domain reasoning with Amazon Bedrock AgentCore Browser Tool for live portal interaction. This approach preserves human expertise while removing repetitive screen work. Link to article: …


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  • Build an agentic incident triage assistant with Amazon Quick and New Relic

    calendar Jun 9, 2026 · aws.amazon.com/blogs/machine-learning
    Build an agentic incident triage assistant with Amazon Quick and New Relic

    This post shows engineering teams how to apply that principle to one of the most time-sensitive workflows in engineering: incident triage. You will build a custom incident triage assistant agent using Amazon Quick that orchestrates a response with the New Relic Model Context Protocol (MCP) Server and Asana through …


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  • Unlocking AI flexibility in Europe: A guide to cross-region inference for EU data processing and model access

    calendar Jun 8, 2026 · aws.amazon.com/blogs/machine-learning
    Unlocking AI flexibility in Europe: A guide to cross-region inference for EU data processing and model access

    With access to the latest generative AI models and high-performance accelerated compute in high global demand, AWS customers need tools to take advantage of model availability and capacity across multiple AWS Regions, while still meeting their security and privacy requirements. cross-Region Inference (CRIS) on Amazon …


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  • It’s safe to close your laptop now: Hosting coding agents on Amazon Bedrock AgentCore

    calendar Jun 8, 2026 · aws.amazon.com/blogs/machine-learning
    It’s safe to close your laptop now: Hosting coding agents on Amazon Bedrock AgentCore

    Amazon Bedrock AgentCore Runtime gives each agent session its own isolated microVM with a persistent workspace, secure tool access through Gateway, and built-in observability—so you can run Claude Code, Codex, Kiro, and Cursor in parallel without sharing secrets, ports, or filesystems. Close the lid, go to dinner, and …


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  • Better decisions at scale: How mathematical optimization delivers where intuition fails

    calendar Jun 8, 2026 · aws.amazon.com/blogs/machine-learning
    Better decisions at scale: How mathematical optimization delivers where intuition fails

    In this post, we introduce mathematical optimization, explain how it fits within the broader AI landscape, and showcase real-world success stories where the Innovation Center has partnered with customers to deliver concrete results. Link to article: …


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  • End-to-end encrypted ML inference with Amazon SageMaker AI and FHE

    calendar Jun 8, 2026 · aws.amazon.com/blogs/machine-learning
    End-to-end encrypted ML inference with Amazon SageMaker AI and FHE

    This blog has previously discussed FHE for ML inference in the post Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing, but this post goes a little further. That previous post showed how to implement FHE-based inference 'from scratch' by hand-crafting a …


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  • Amazon Quick ARNs: Cross-account migration and namespace permissions

    calendar Jun 8, 2026 · aws.amazon.com/blogs/machine-learning
    Amazon Quick ARNs: Cross-account migration and namespace permissions

    In this post, we cover the structure of Amazon Quick ARNs and provide a practical mental model for working with them. By the end, you can look at an ARN and immediately understand what it means for your migration strategy, diagnose permission issues faster, and design multi-tenant architectures with confidence. Link to …


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  • Evaluate your Amazon Nova Sonic voice agent at scale, no microphone required

    calendar Jun 8, 2026 · aws.amazon.com/blogs/machine-learning
    Evaluate your Amazon Nova Sonic voice agent at scale, no microphone required

    In this post, we walk you through the Nova Sonic Test Harness, an open source framework that we built to solve both problems. It serves as a rapid iteration tool for tuning system prompts and tool configurations (run a conversation, see results, adjust, repeat) and as a comprehensive evaluation framework for validating …


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