AWSML

The North Star Every organization racing to deploy AI agents faces the same reckoning: an agent that demos beautifully can quietly degrade in production, and by the time a human notices, the trust is already broken. Where traditional software fails loudly, agents fail softly. They return an answer that looks confident, reads fluently, and is … Read more

Reflection AI introduced Beam, an open-weight model for agentic coding and long-horizon tasks such as maintaining code, using tools, interpreting results, and completing multi-step workflows. The open-weight release gives developers and researchers control over the runtime, deployment environment, and customization process. In this post, we explain Reflection’s vision and show how you can deploy Beam … Read more

Muse Spark Open, Meta’s coding-optimized open-weight model, is now available in Amazon SageMaker JumpStart, the machine learning (ML) hub of Amazon SageMaker AI. The model was trained on real developer workflows, such as multi-file refactors and long debugging sessions, and it supports a context window of 1 million tokens. You can deploy it to a … Read more

In every conversation I have with enterprise leaders, they say the same thing. They want agents to do more, but they don’t trust them to do it right all the time. That’s fair. The same creativity and autonomy that makes agents useful makes them hard to trust. Give an agent a task and it finds … Read more

IDC research shows that document-related challenges cost organizations $19,732 for each information worker annually and reduce productivity by 21.3 percent. Organizations receiving invoices from hundreds of suppliers often face layouts that vary by issuer and change without notice. Template-based systems require constant maintenance at this scale. Staff can spend up to 30 percent of their … Read more

A financial services team spends significant time each week manually creating client PowerPoint presentations from quarterly reports, compliance documents, and market analyses. Each presentation requires reading hundreds of pages, extracting key data points, structuring slides, and generating supporting visuals. This post walks you through building an AI agent system using Amazon Bedrock AgentCore that automates … Read more

Critical cloud exposures pile up faster than security teams can close them. Cloud-native application protection platforms (CNAPP), cloud providers, and posture scanners generate more findings than any team can triage, and risk accumulates in the gap between detected and fixed. Most findings sit untouched, not because they’re hard to fix. Someone must investigate context, identify … Read more

Choosing the right model for a specific application requires a practical way to test it with representative inputs. Amazon SageMaker JumpStart provides access to a broad catalog of already pretrained models. In this post, we show how to deploy an available model from SageMaker JumpStart, run a lightweight and repeatable performance test using the SageMaker … Read more

AI agents increasingly need to access web resources that are priced per request. For example, premium datasets charge by the query, research APIs meter by the call, and paywalled publishers gate content behind payment. When an AI agent encounters one of these resources, the server returns HTTP 402 Payment Required. The agent has no built-in … Read more

Managing AI model access across dozens or hundreds of AWS accounts creates operational friction when each workload account must subscribe and accept AWS Marketplace Private Pricing Offers (MPPOs) individually. Amazon Bedrock with managed entitlements simplifies multi-account access to third-party AI models so you can subscribe once from a central account and distribute access across your … Read more

Security analysts need fast answers about their cloud infrastructure without deep familiarity with domain-specific query languages. Orca Security’s tool covers over 900 cloud models (the resource types Sonar tracks, such as an Amazon Elastic Compute Cloud (Amazon EC2) instance or an Amazon Simple Storage Service (Amazon S3) bucket). Querying that data required precise model names, … Read more

This post is co-written with Kenneth Salmon, Edward Boswell, Jack Armstrong, Robert Bahn, and Nick Ciubotariu from ShipStation Global. Answering the same IT questions and clearing routine tickets drains time that IT teams could spend elsewhere. To reclaim it, the ShipStation Global Engineering team built Deckhand, an AI-powered IT help desk agent for Slack, on … Read more

SpaceXAI’s Grok 4.7 is now available on Amazon Bedrock, which offers a choice of foundation models (FMs) from multiple providers. According to SpaceXAI, Grok 4.7 is trained to work longer on more difficult tasks and knows when to check its own work. That matters most for agents, which carry a task through many steps and … Read more

Mixture-of-Experts (MoE) is a sparsely-activated architecture that scales large language model (LLM) capacity while keeping per-token compute low. Because its operations account for a large share of total compute time, inefficiencies there directly raise request latency and cost. Therefore, optimizing MoE operations through kernel engineering offers the largest opportunity for performance gains. Fused MoE is … Read more

Single-Region inference can throttle when demand exceeds local capacity. Teams in Thailand, Malaysia, Singapore, Indonesia, and Taiwan need access to the newest OpenAI models beyond that capacity. Amazon Bedrock offers OpenAI GPT-6 Sol and GPT-6 Luna through global cross-Region inference from all five AWS Regions, and GPT-6 Astra from Asia Pacific (Singapore). This post shows … Read more

Applications that route requests, select agent actions, or assign policy outcomes often need scores over a fixed set of choices instead of free-form text. Deploying these decision models with llama.cpp on Amazon SageMaker AI gives you a managed path for serving quantized models on CPU or GPU infrastructure. This post continues a series on specialized … Read more

This post shows how to deploy one large language model (LLM) across two GPU nodes on Amazon Elastic Kubernetes Service (Amazon EKS) with the multi-node Ray LLM Deep Learning Containers. It uses separate prefill and decode nodes behind one OpenAI-compatible endpoint. This kind of multi-node setup is common for tensor, pipeline, and data parallelism, as … Read more

A recap of the latest Amazon Bedrock, Amazon Bedrock AgentCore, and Strands updates from September 2026 At AWS, we believe the fastest path to enterprise AI is giving builders real choice at every layer: model, runtime, and tooling. That belief shapes how we invest across Amazon Bedrock, AgentCore, and Strands. Amazon Bedrock continues expanding access … Read more

Building an AI agent for a demo and operating one for 40 million developers are different engineering problems. Postman set out to build Agent Mode, an AI-native way to work across API testing, documentation, discovery, and implementation. The team expected model quality and prompt design to be the hardest problems. The deeper challenges came from … Read more

When an AI agent runs, it often needs to buy something to finish a task: a model inference, an API response, access web content, or a call to another agent. These purchases are small and frequent, sometimes a fraction of a cent each, and they happen inside the agent’s loop with no person available to … Read more

Multiple teams within the same company increasingly need shared access to expensive GPU clusters for their generative AI operations, while maintaining isolation boundaries, resource fairness, and operational independence. Consider a data science team training large language models, a computer vision group running inference workloads, and a research team experimenting with new model architectures. All of … Read more

Today, we’re excited to announce the availability of Claude Haiku 5.5 on Amazon Bedrock and Claude Platform on AWS. According to Anthropic, Claude Haiku 5.5 is the fastest and most efficient model in the Claude 5.5 family, built for subagents and high-volume, cost-sensitive work. It also costs around 75 percent less than Claude Haiku 4.5 … Read more

Enterprise organizations are adopting Retrieval Augmented Generation (RAG) to unlock insights from company knowledge sources like Microsoft SharePoint, Google Drive, and Atlassian Confluence. However, these knowledge sources contain sensitive information governed by complex permission structures. Making sure that AI-generated answers respect those permissions is one of the hardest challenges in enterprise AI. In this post, … Read more

Agentic automation, software that reasons and adapts to complete tasks, is showing up on AI center of excellence (AI CoE) roadmaps. But the standard way companies justify automation investments, hours saved times labor cost minus build cost, was designed for rule-based tools like robotic process automation (RPA). That model misses most of the value agents … Read more

Building grounded AI on Amazon Bedrock, Qlik Answers tackles a common enterprise problem: employees aren’t short on data. They are short on a fast way to ask a real question of it and get an answer they can trust. Analysts spend hours searching through documents, dashboards, and institutional memory to answer things a colleague could … Read more

Reducing the time between incident detection, investigation, and remediation is a critical priority for organizations running production workloads on AWS. When an issue arises, on-call engineers often need to quickly diagnose the problem across application components, identify the root cause, and apply the fix, often in the middle of the night. AWS DevOps Agent, an … Read more

The biggest barrier to AI adoption isn’t awareness. It’s the gap between talking about AI and building with it. Professionals whose primary role isn’t writing code, but whose daily work increasingly depends on AI solutions, don’t need engineering backgrounds to start building AI capability. They need the right tools, structured support, and permission to fail. … Read more

Cornerstone OnDemand, Inc. (Cornerstone) is a global leader in workforce readiness solutions, serving 140 million users across 186 countries. The company built a multi-agent AI system that transforms database operations from reactive firefighting into proactive, self-orchestrating workflows. The system, called Orion AI, uses Amazon Bedrock and Strands Agents, an open source agent orchestration framework from … Read more

Off-the-shelf AI assistants answer individual questions well, but they fall short on a different axis: continuity. Ask a stateless assistant about your garden today and it has no idea that you mentioned your fast-draining raised beds three weeks ago, that you only use organic fertilizer, or that your petunias were struggling through a heat wave. … Read more

With generative AI adoption moving faster than the personal computer or the internet and global AI-related investment in 2025 representing $581.69 billion, organizations must position their workforce to use AI to power their operations while employing it responsibly. Researchers affiliated with the AI Adoption Initiative argue that the workforce relates to AI through an AI … Read more