Blog_dumb

Introducing Web Search on Amazon Bedrock for foundation model grounding

Introducing Web Search on Amazon Bedrock for foundation model grounding

When a foundation model needs to answer a question about last week’s earnings call, yesterday’s regulatory change, or this morning’s weather forecast, it needs knowledge it was never trained on. Grounding the model in current web knowledge closes that gap – whether it’s powering chatbots, coding assistants, CLI tools, or enterprise applications, grounding helps answer

Introducing Web Search on Amazon Bedrock for foundation model grounding Read More »

Automated web insight extraction with Amazon Bedrock AgentCore

Automated web insight extraction with Amazon Bedrock AgentCore

Extracting insights from dozens of websites often means manually checking each one, a process that quickly becomes overwhelming. Design teams need to track competitor products, marketing teams want to monitor content trends, and product managers need to stay on top of market intelligence. But doing this manually means someone has to visit sites, copy content,

Automated web insight extraction with Amazon Bedrock AgentCore Read More »

From weeks to minutes: How Formula 1® uses agentic AI on AWS to accelerate data operations

From weeks to minutes: How Formula 1® uses agentic AI on AWS to accelerate data operations

Formula 1® (F1) engages an audience of over 800 million fans globally across digital platforms, F1 TV, social media, ticketing, and merchandise year-round. Races happen every two weeks. Fan engagement windows are measured in minutes and commercial decisions need to move at the speed of the grid. Behind the scenes, F1’s marketing technology (MarTech) platform, Customer

From weeks to minutes: How Formula 1® uses agentic AI on AWS to accelerate data operations Read More »

Automated Reasoning policy refinement in Amazon Bedrock

Automated Reasoning policy refinement in Amazon Bedrock

Refining an Automated Reasoning policy in Amazon Bedrock has been a manual cycle of diagnose, hand-edit, retest, and repeat. Today, we are announcing automatic policy refinement, which automates the diagnose-and-fix work in that cycle. The refinement engine diagnoses failing tests and proposes formal-logic fixes. You approve every change before it takes effect. Automated Reasoning checks

Automated Reasoning policy refinement in Amazon Bedrock Read More »

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

Announcing the Agentic Catalog Experience in Amazon Quick Read More »

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

Optimizing production agents with Amazon Bedrock AgentCore Observability Read More »

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

Deploying Kimi K3 on AWS Read More »

Scroll to Top