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Announcing the Agentic Catalog Experience in Amazon Quick

Announcing the Agentic Catalog Experience in Amazon Quick

As organizations embrace AI-powered analytics, the value of a natural language (Text2SQL) answer is only as good as the business context behind it. We’re entering a phase where semantic richness (table and column descriptions, and relationships) must flow directly from where it’s authored in upstream data catalogs and semantic tools into the AI products that […]

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Optimizing production agents with Amazon Bedrock AgentCore Observability

Optimizing production agents with Amazon Bedrock AgentCore Observability

As your AI agents move from prototype to production, the challenges shift from getting them to work to keeping them fast and efficient. In Part 1 of this series, we walked through debugging two common agent failures: infinite loops and tool invocation errors. Those scenarios dealt with agents that were broken. In this post, we

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Deploying Kimi K3 on AWS

Deploying Kimi K3 on AWS

Open weight models have become powerful enough to handle complex tasks such as multi-step agentic workflows, advanced reasoning, and long-horizon coding. However, as these models grow in capability, they also grow in size and hosting multi-trillion parameter architectures requires purpose-built infrastructure, high-end GPU compute, and optimized serving frameworks. On July 27, 2026, Moonshot AI released

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How Yahoo enhances search retargeting using Amazon Bedrock

How Yahoo enhances search retargeting using Amazon Bedrock

Connecting user search intent with relevant ad experiences across channels is a longstanding challenge in digital advertising. Advertisers need sophisticated ways to reach audiences based on their demonstrated interests and behaviors, particularly their search activity, which is one of the strongest signals of user intent. Traditional keyword expansion approaches often struggle with outdated vocabulary, limited

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Inference meta-monitoring for Amazon SageMaker AI endpoints with Amazon Quick

Inference meta-monitoring for Amazon SageMaker AI endpoints with Amazon Quick

Without the ability to track machine learning (ML) model prediction quality, organizations only realize they have issues when their customers complain or when they conduct spot checks, which jeopardizes customer trust. This post introduces inference meta-monitoring for Amazon SageMaker AI endpoints. It provides a governance layer that sits above production ML inference pipelines to continuously

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Introducing explicit prompt caching for OpenAI GPT-5.6 models on Amazon Bedrock

Introducing explicit prompt caching for OpenAI GPT-5.6 models on Amazon Bedrock

This post is co-written with Chris Dickens from OpenAI. OpenAI GPT-5.6 Sol, Terra, and Luna are now generally available on Amazon Bedrock. With GPT-5.6 on Amazon Bedrock, you get the newest generation of OpenAI frontier models with pay-per-token pricing, AWS security and governance controls, and usage that counts toward your existing AWS commitments. The family

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Migrate your prompts to new models and optimize them on Amazon Bedrock

Migrate your prompts to new models and optimize them on Amazon Bedrock

The problem: Prompt engineering at scale is still painful Migrating prompts to new models on Amazon Bedrock, or optimizing them for your current model, is still one of the most manual parts of building a generative AI application. Say you have built a deployed generative AI application. It works. Your prompts are tuned, your outputs

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Authenticate with Private Key JWT using Amazon Bedrock AgentCore Identity

Authenticate with Private Key JWT using Amazon Bedrock AgentCore Identity

Amazon Bedrock AgentCore Identity now supports Private Key JWT client authentication for agents. With Private Key JWT client authentication, your agents can authenticate to a downstream identity provider’s token endpoint using a signed JSON Web Token (JWT) client assertion instead of a shared OAuth 2.0 client secret. You can register a public key with your

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Generate Autonomous Business Insights with AI Agent and MCP Servers

Generate Autonomous Business Insights with AI Agent and MCP Servers

A Monday morning problem Sarah Chen manages 12 assembly lines and 2,000 machines. Before her 10 AM production review, she needs one answer: Which lines need attention this week? Simple question. Painful journey. She starts in the IoT dashboard. Line 4’s motor temperature is running 12°C above baseline — has been for three days. Calibration

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Automating customer retention workflows in Amazon Quick

Automating customer retention workflows in Amazon Quick

Automating customer retention workflows in Amazon Quick can turn a five-day churn-response cycle into one that takes minutes. Last quarter, a mid-size SaaS company lost 12% of its at-risk accounts because the retention team took five days to identify and contact dissatisfied customers. By the time someone manually reviewed CSAT spreadsheets and call transcripts, those

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