AWSML

To power up AI workflows on Amazon Elastic Kubernetes Service (Amazon EKS), data scientists need interactive IDEs like JupyterLab and Code Editor. Yet running those IDEs usually means leaving the cluster that hosts their pipelines, moving to a standalone JupyterHub deployment or a local laptop. That switch leaves them without the GPU nodes, shared storage, … Read more

nOps, an AI-powered cloud optimization solution, recently reimagined its Financial Operations (FinOps) analytics capabilities by transitioning to Amazon Bedrock AgentCore. Amazon Bedrock AgentCore is a service to build, connect, and optimize agents at scale, with any framework or model. The new foundation helps nOps better serve customers managing commitment optimization across Amazon Web Services (AWS), … Read more

Prior authorization is the approval process health plans require before covering certain medical services or medications. It remains one of the most manual processes in healthcare, not because the medical reasoning for requiring approval is flawed, but because the policies that govern it are trapped in static, unstructured formats that resist automation. This content is … Read more

This is a guest post co-written with Vitaly Omelchenko from the TReNDS Center at Georgia State University. At the Center for Translational Research in Neuroimaging and Data Science (TReNDS), a joint center of Georgia State University, Georgia Institute of Technology, and Emory University, we develop and apply advanced analytical methods and neuroinformatics tools for brain … Read more

As the National Hockey League (NHL) regular season enters its final stretch each spring, one question dominates the minds of hockey fans: has my team clinched the playoffs? The answer is often surprisingly hard to discern. With 32 teams, complex tie-breaking rules, and hundreds of remaining games, determining whether a team is mathematically guaranteed a … Read more

Before AI agents, it was generally sufficient for access controls to treat each action as an independent event. Applications relied on deterministic business logic to enforce whether actions happened in the right order or whether the data was up-to-date. AI agents behave in fundamentally different ways than traditional applications. They decide at runtime which tools … Read more

Amazon Bedrock AgentCore gateway is a fully managed, serverless AI gateway that provides a single, secure entry point for AI traffic. AgentCore gateway routes traffic to tools such as managed web search, managed knowledge bases, MCP servers, inference models (LLMs), agents (A2A, agents as tools, etc.), or HTTP endpoint. Today, we are announcing support for … Read more

Agents are becoming more autonomous and teams are running more of them, but trust and security have not kept pace. According to McKinsey, roughly 80% of organizations have already encountered risky behavior from AI agents. As a result, security and risk concerns are the leading barrier to scaling agentic AI (McKinsey’s State of AI Trust … Read more

As organizations move from experimenting with coding agents to adopting them across engineering teams, the leadership question changes. It is no longer only, “Can this tool help a developer?” It becomes, “How do we understand adoption, manage consumption, maintain reliability, and scale access responsibly?”. Codex can emit OpenTelemetry (OTel) metrics about its activity. When local … Read more

A US-headquartered global organization recently came to us with a deceptively simple data-residency request: let their engineers use Claude Code. The requirement: Amazon Bedrock model inference had to be processed in London (the eu-west-2 AWS Region), not merely called from London. Their compliance team had drawn a hard line. Prompts, completions, and intermediate processing were … Read more

Teams that adopt Amazon Bedrock Automated Reasoning checks often want to run the policy lifecycle in code. Running it in code keeps the work repeatable, reviewable, and driven by the coding agent they already use. Authoring a good Automated Reasoning policy has a learning curve, and the lifecycle has constraints that can trip you up. … Read more

Many enterprises have a long tail of internal tools that never get built. A team needs a shipping-cost calculator, a straightforward intake form, a small dashboard over a spreadsheet, but each one requires a developer, a backlog slot, and a deployment pipeline. The tools are too small to prioritize and too numerous to ignore. PDI … Read more

Buying a home is one of the biggest financial decisions most people face, and LendingTree built a multi-agent mortgage assistant on Amazon Bedrock to make the process more straightforward. The assistant educates borrowers, understands their situation, and provides tailored options in a natural conversation. Borrowers must weigh purchase or refinance, conventional or government-backed, 15-year or … Read more

What if deploying production-grade AI agents required zero infrastructure management, came with enterprise observability built-in, and worked easily with your existing on-premises systems? Mobileye, the autonomous driving pioneer with more than 230 million EyeQ system-on-chips deployed across roughly 1,200 vehicle models worldwide, saw an opportunity to free skilled engineers from routine internal ticket status inquiries. … Read more

Our agent runs in the cloud, but our users’ spreadsheets live on their laptops. How do you bridge that gap? The Model Context Protocol (MCP) is an open source standard introduced by Anthropic in November 2024 to standardize how AI models connect to external data and tools. MCP follows a client-server architecture where an MCP … Read more

If you build and automate workflows in n8n without writing much code, you’ve probably used its AI Agent node to add a model call to a workflow. It’s a great start. But a production agent needs more than a single model call: memory that lasts beyond one run, tools it can actually use like a … Read more

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 … Read more

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, … Read more

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 … Read more

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 … Read more

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 … Read more

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 … Read more

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 … Read more

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 … Read more

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 … Read more

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 … Read more

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 … Read more

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 … Read more

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 … Read more

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 … Read more