Amazon SageMaker HyperPod gives machine learning (ML) teams access to large pools of accelerated compute for training and fine-tuning models. When several teams share one cluster, the technical setup is usually straightforward. The challenging part is governance. You must decide which teams can use the cluster, how much capacity each team gets, what happens when … Read more
We recently introduced the ability to create and manage Amazon SageMaker Spaces on Amazon SageMaker HyperPod EKS clusters directly from the Amazon SageMaker Studio UI. Data scientists and machine learning (ML) engineers can now launch JupyterLab and Code Editor environments on HyperPod clusters without leaving their browser or using command-line tools, reducing the time from … Read more
Airlines already have apps and websites where travelers check flights, pick seats, and manage bookings, and adding a natural voice layer opens those tasks to spoken requests. With this voice layer, a traveler can change a seat or check a delay by speaking, without leaving the app or navigating through screens. Building it requires careful … Read more
Coding and agentic workloads are asking more of AI models than ever: refactor a repository spanning hundreds of files, sustain a multi-hour agentic workflow without losing context, and reason through complex systems problems with tool use at every step. Meeting those demands with open-weight models has historically meant provisioning and operating your own inference infrastructure. … Read more
Engineers increasingly use coding assistance tools to accelerate their development workflows. Today, Amazon SageMaker AI optimized generative AI inference introduces the aws-ai-ml skill, available through the Agent Toolkit for AWS. This skill gives coding agents like Kiro, Claude Code, and Codex deep expertise in inference optimization and benchmarking. Install the skill, and your existing agent … Read more
Amazon Quick is Amazon’s agentic AI companion built for work. You build agents that reason over your data, call action connectors, and carry multi-step tasks to completion. Promoting those resources (chat agents, action connectors, knowledge bases, flows, and spaces) from a development to a production AWS account, the way you would any other application, has … Read more
When a user asks the support assistant, a Retrieval Augmented Generation (RAG) application built with LangChain to compare two products across three dimensions, they’re effectively posing six questions simultaneously. Similarity search uses a single query vector to encapsulate all the intents. The retriever then generates the best approximation of the average of those intents. The … Read more
Managing access permissions effectively is an important aspect of maintaining a secure and collaborative environment in Amazon Quick. Quick supports versatile user management options designed to accommodate various identity types and organizational needs. You can provision users natively through Quick Identity or manage them through enterprise identity providers such as AWS IAM Identity Center or … Read more
A critical challenge that emerges as multi-agent systems move from experimentation to production is making sure that these systems are consistently helpful, accurate, and explainable in real-world scenarios. Enterprises are increasingly adopting multi-agent systems to solve complex, real-world problems that require reasoning across data sources, tools, and business constraints. From supply chain planning to financial … Read more
Checking tens of thousands of apartment leases against constantly changing state landlord-tenant laws, and proving you actually checked all of them, has been beyond the reach of most compliance teams. But with generative AI in Amazon Quick, paired with the right backend, it’s now possible. In this post, we introduce a design pattern called Adjudicated … Read more
Claude Desktop on Amazon Bedrock provides powerful AI assistance, but without integrated web search, responses are limited to the model’s training knowledge cutoff. When you need current information, such as recent documentation updates, live pricing, or weather updates, the model can’t retrieve it on its own. Amazon Bedrock AgentCore is a platform to build, connect, … Read more
Search agents powered by large language models (LLMs) are transforming how enterprises retrieve information. Rather than requiring users to craft the perfect query, a search agent autonomously decides what to search for, which retrieval strategy to use, and when to stop searching. It does this across multiple rounds of interaction, refining its approach based on … Read more
Quick Apps could already bring live data into an app from connectors and content sources: action connectors (services like Jira, Slack, and Google Drive), Spaces documents, web search, and AI inference all run at view time, not build time. The solution introduces live structured data from your data lakes, databases, and other analytics data stores. … Read more
In my previous post: Building persistent memory for multi-agent AI systems with Amazon S3 Vectors, we explored why memory engineering is the foundational discipline for production multi-agent systems. We showed how Amazon S3 Vectors, a capability of Amazon Simple Storage Service (Amazon S3), meets the architectural requirements for agent memory: semantic retrieval, rich metadata, strong … Read more
Generative AI has made it possible to produce large amounts of personalized content quickly and at low cost. In our previous post, we showed how generative AI on Amazon Bedrock can produce personalized content at scale while staying within brand guidelines and guardrails. The new challenge is now one of selection. Among all of those … Read more
Teams that process documents at scale know the routine: files land in storage, someone notices, opens each one, decides what it needs, and routes it for review. Monitoring alerts queue up the same way, waiting for a person to act on them. The hours lost to manual triage are the operational problem ambient agents solve. … Read more
You need Claude Platform on AWS (CPonAWS) inference from three environments: production workloads on AWS, developer laptops for local iteration, and external services on other cloud providers or on-premises continuous integration and continuous delivery (CI/CD) pipelines. Each environment has different authentication requirements, but all should share a single subscription with workspace-level isolation between production and … Read more
Amazon Quick Sight is a fully managed, cloud-native business intelligence (BI) capability for building and publishing interactive dashboards. You can access these dashboards from any device and embed them into your applications, portals, and websites. When building a dashboard, authors add filters so readers can narrow the data to what they want to analyze. But … Read more
uniopen is a digital communication and membership platform launched by Taiwan’s Uni-President Enterprises Group, connecting customers to ecommerce, membership benefits, and other retail experiences across web, tablet, and mobile channels. Across those channels, uniopen applies a moderation policy that classifies each interaction along two axes. The first is what behavior occurred (nine categories), and the … Read more
Claim answers are scattered across adjuster diary entries, repair estimates, police reports, payment ledgers, and scanned attachments rather than one searchable field. A policyholder might ask whether a claim was approved, while an adjuster might need every open auto claim over $10,000 from last month. Both tasks require finding and combining evidence quickly and accurately. … Read more
As organizations move from single-purpose agents to multi-agent systems, the infrastructure requirements change. A lone agent handling customer queries can run in a serverless environment with short-lived sessions. But when you need three agents collaborating on a creative workflow that spans several days, sharing context and building on each other’s output, serverless sessions that cap … Read more
We’re excited to announce the availability of Anthropic’s Claude Opus 5, Claude Sonnet 5, and Claude Haiku 4.5 in India. The India regional endpoint is served through geographic cross-Region inference. Customers in India can now access these models on Amazon Bedrock while processing the data in the India Regions in addition to the already supported … Read more
Amazon Bedrock now supports the Anthropic Claude models: Claude Opus 5 and Claude Sonnet 5 in Seoul and Claude Sonnet 5 in Singapore with in-region inference on the bedrock-runtime endpoint. If you have local data processing requirements in South Korea or Singapore, for example, in financial services, healthcare, and the public sector, you can now … Read more
GPT-6.1 Sol is now generally available on Amazon Bedrock, bringing stronger reasoning to coding, computer use, and professional workloads that run frequently. For an AI agent to complete a task, it may need to gather information, use tools, test different approaches, recover from errors, and verify its result. Every decision shapes what happens next. A … Read more
Prompt engineering in Amazon Quick determines how accurately and reliably the platform’s AI-powered features respond to your natural-language requests. Whether you’re building custom agents, authoring automation flows, or querying data through conversational analytics, the way you structure your prompts directly shapes the quality of the output you receive. In this post, you will learn the … Read more
In Part 1 of this series, we covered the foundational principles of prompt engineering in Amazon Quick: specificity, context-setting, few-shot examples, and the CRISPE framework for complex requests. Those principles apply universally. In this post, we go component by component, showing you how each Quick capability interprets prompts differently and what patterns get the best … Read more
You’re a director of contracting, responsible for hundreds, maybe thousands, of vendor contracts. Each one is packed with critical data: contract values, expiration dates, signing status, and key contacts. With that information locked inside PDFs, you and your team spend hours manually extracting it, maintaining spreadsheets, and fielding the same recurring questions: “Which vendor are … Read more
Condé Nast’s editorial teams had no fast way to do multimodal video discovery. They were spending an average of 250 minutes per content discovery task, manually scrubbing through a library of more than 140,000 videos. They relied on titles and descriptions to find relevant clips. In a media environment where speed-to-market directly determines revenue capture, … Read more
xAI’s Grok 4.7 is now available on Amazon Bedrock, adding a frontier model built for coding, long-running agents, and knowledge work to the Bedrock model catalog. It offers a 500K token context window and supports configurable reasoning effort at four levels: low, medium, high, and xhigh. Grok 4.7 is served on the bedrock-runtime endpoint through … Read more
Today, we’re excited to announce the availability of Claude Sonnet 5.5 on Amazon Bedrock and Claude Platform on AWS. Claude Sonnet 5.5 is a smarter, more efficient Sonnet model suited for focused coding and knowledge work with lower cost per task for most work at faster speed. Amazon Bedrock gives you Sonnet 5.5 capabilities while … Read more