• Open

    Automate Amazon QuickSight data stories creation with agentic AI using Amazon Nova Act
    In this post, we demonstrate how Amazon Nova Act automates QuickSight data story creation, saving time so you can focus on making critical, data-driven business decisions.  ( 37 min )
    Implement automated monitoring for Amazon Bedrock batch inference
    In this post, we demonstrated how a financial services company can use an FM to process large volumes of customer records and get specific data-driven product recommendations. We also showed how to implement an automated monitoring solution for Amazon Bedrock batch inference jobs. By using EventBridge, Lambda, and DynamoDB, you can gain real-time visibility into batch processing operations, so you can efficiently generate personalized product recommendations based on customer credit data.  ( 39 min )

  • Open

    Responsible AI: How PowerSchool safeguards millions of students with AI-powered content filtering using Amazon SageMaker AI
    In this post, we demonstrate how PowerSchool built and deployed a custom content filtering solution using Amazon SageMaker AI that achieved better accuracy while maintaining low false positive rates. We walk through our technical approach to fine tuning Llama 3.1 8B, our deployment architecture, and the performance results from internal validations.  ( 40 min )

  • Open

    Unlock global AI inference scalability using new global cross-Region inference on Amazon Bedrock with Anthropic’s Claude Sonnet 4.5
    Organizations are increasingly integrating generative AI capabilities into their applications to enhance customer experiences, streamline operations, and drive innovation. As generative AI workloads continue to grow in scale and importance, organizations face new challenges in maintaining consistent performance, reliability, and availability of their AI-powered applications. Customers are looking to scale their AI inference workloads across […]  ( 43 min )
    Secure ingress connectivity to Amazon Bedrock AgentCore Gateway using interface VPC endpoints
    In this post, we demonstrate how to access AgentCore Gateway through a VPC interface endpoint from an Amazon Elastic Compute Cloud (Amazon EC2) instance in a VPC. We also show how to configure your VPC endpoint policy to provide secure access to the AgentCore Gateway while maintaining the principle of least privilege access.  ( 44 min )

  • Open

    Enhance agentic workflows with enterprise search using Kore.ai and Amazon Q Business
    In this post, we demonstrate how organizations can enhance their employee productivity by integrating Kore.ai’s AI for Work platform with Amazon Q Business. We show how to configure AI for Work as a data accessor for Amazon Q index for independent software vendors (ISVs), so employees can search enterprise knowledge and execute end-to-end agentic workflows involving search, reasoning, actions, and content generation.  ( 41 min )
    Accelerate development with the Amazon Bedrock AgentCore MCP server
    Today, we’re excited to announce the Amazon Bedrock AgentCore Model Context Protocol (MCP) Server. With built-in support for runtime, gateway integration, identity management, and agent memory, the AgentCore MCP Server is purpose-built to speed up creation of components compatible with Bedrock AgentCore. You can use the AgentCore MCP server for rapid prototyping, production AI solutions, […]  ( 37 min )

  • Open

    How Hapag-Lloyd improved schedule reliability with ML-powered vessel schedule predictions using Amazon SageMaker
    In this post, we share how Hapag-Lloyd developed and implemented a machine learning (ML)-powered assistant predicting vessel arrival and departure times that revolutionizes their schedule planning. By using Amazon SageMaker AI and implementing robust MLOps practices, Hapag-Lloyd has enhanced its schedule reliability—a key performance indicator in the industry and quality promise to their customers.  ( 41 min )
    Rox accelerates sales productivity with AI agents powered by Amazon Bedrock
    We’re excited to announce that Rox is generally available, with Rox infrastructure built on AWS and delivered across web, Slack, macOS, and iOS. In this post, we share how Rox accelerates sales productivity with AI agents powered by Amazon Bedrock.  ( 37 min )
  • Open

    September 2025
    Pupdate Autumn is upon us, and it was a wet start to the month, but that hasn’t stopped the boys from being enthusiastic about their walks. Clear scan Milo had another scan at the start of the month, and once again it was clear :) That means we’re now on the longest stretch of remission […]  ( 14 min )

  • Open

    Modernize fraud prevention: GraphStorm v0.5 for real-time inference
    In this post, we demonstrate how to implement real-time fraud prevention using GraphStorm v0.5's new capabilities for deploying graph neural network (GNN) models through Amazon SageMaker. We show how to transition from model training to production-ready inference endpoints with minimal operational overhead, enabling sub-second fraud detection on transaction graphs with billions of nodes and edges.  ( 43 min )

  • Open

    Building health care agents using Amazon Bedrock AgentCore
    In this solution, we demonstrate how the user (a parent) can interact with a Strands or LangGraph agent in conversational style and get information about the immunization history and schedule of their child, inquire about the available slots, and book appointments. With some changes, AI agents can be made event-driven so that they can automatically send reminders, book appointments, and so on.  ( 40 min )
    Build multi-agent site reliability engineering assistants with Amazon Bedrock AgentCore
    In this post, we demonstrate how to build a multi-agent SRE assistant using Amazon Bedrock AgentCore, LangGraph, and the Model Context Protocol (MCP). This system deploys specialized AI agents that collaborate to provide the deep, contextual intelligence that modern SRE teams need for effective incident response and infrastructure management.  ( 47 min )

  • Open

    DoWhile loops now supported in Amazon Bedrock Flows
    Today, we are excited to announce support for DoWhile loops in Amazon Bedrock Flows. With this powerful new capability, you can create iterative, condition-based workflows directly within your Amazon Bedrock flows, using Prompt nodes, AWS Lambda functions, Amazon Bedrock Agents, Amazon Bedrock Flows inline code, Amazon Bedrock Knowledge Bases, Amazon Simple Storage Service (Amazon S3), […]  ( 39 min )
    How PropHero built an intelligent property investment advisor with continuous evaluation using Amazon Bedrock
    In this post, we explore how we built a multi-agent conversational AI system using Amazon Bedrock that delivers knowledge-grounded property investment advice. We explore the agent architecture, model selection strategy, and comprehensive continuous evaluation system that facilitates quality conversations while facilitating rapid iteration and improvement.  ( 39 min )
    Accelerate benefits claims processing with Amazon Bedrock Data Automation
    In the benefits administration industry, claims processing is a vital operational pillar that makes sure employees and beneficiaries receive timely benefits, such as health, dental, or disability payments, while controlling costs and adhering to regulations like HIPAA and ERISA. In this post, we examine the typical benefit claims processing workflow and identify where generative AI-powered automation can deliver the greatest impact.  ( 40 min )

  • Open

    Running deep research AI agents on Amazon Bedrock AgentCore
    AI agents are evolving beyond basic single-task helpers into more powerful systems that can plan, critique, and collaborate with other agents to solve complex problems. Deep Agents—a recently introduced framework built on LangGraph—bring these capabilities to life, enabling multi-agent workflows that mirror real-world team dynamics. The challenge, however, is not just building such agents but […]  ( 39 min )
    Integrate tokenization with Amazon Bedrock Guardrails for secure data handling
    In this post, we show you how to integrate Amazon Bedrock Guardrails with third-party tokenization services to protect sensitive data while maintaining data reversibility. By combining these technologies, organizations can implement stronger privacy controls while preserving the functionality of their generative AI applications and related systems.  ( 41 min )

  • Open

    Rapid ML experimentation for enterprises with Amazon SageMaker AI and Comet
    In this post, we showed how to use SageMaker and Comet together to spin up fully managed ML environments with reproducibility and experiment tracking capabilities.  ( 41 min )

  • Open

    Move your AI agents from proof of concept to production with Amazon Bedrock AgentCore
    This post explores how Amazon Bedrock AgentCore helps you transition your agentic applications from experimental proof of concept to production-ready systems. We follow the journey of a customer support agent that evolves from a simple local prototype to a comprehensive, enterprise-grade solution capable of handling multiple concurrent users while maintaining security and performance standards.  ( 49 min )

  • Open

    Scale visual production using Stability AI Image Services in Amazon Bedrock
    This post was written with Alex Gnibus of Stability AI. Stability AI Image Services are now available in Amazon Bedrock, offering ready-to-use media editing capabilities delivered through the Amazon Bedrock API. These image editing tools expand on the capabilities of Stability AI’s Stable Diffusion 3.5 models (SD3.5) and Stable Image Core and Ultra models, which […]  ( 38 min )
    Prompting for precision with Stability AI Image Services in Amazon Bedrock
    Amazon Bedrock now offers Stability AI Image Services: 9 tools that improve how businesses create and modify images. The technology extends Stable Diffusion and Stable Image models to give you precise control over image creation and editing. Clear prompts are critical—they provide art direction to the AI system. Strong prompts control specific elements like tone, […]  ( 43 min )
    Monitor Amazon Bedrock batch inference using Amazon CloudWatch metrics
    In this post, we explore how to monitor and manage Amazon Bedrock batch inference jobs using Amazon CloudWatch metrics, alarms, and dashboards to optimize performance, cost, and operational efficiency.  ( 37 min )
    Use AWS Deep Learning Containers with Amazon SageMaker AI managed MLflow
    In this post, we show how to integrate AWS DLCs with MLflow to create a solution that balances infrastructure control with robust ML governance. We walk through a functional setup that your team can use to meet your specialized requirements while significantly reducing the time and resources needed for ML lifecycle management.  ( 114 min )

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    Supercharge your organization’s productivity with the Amazon Q Business browser extension
    In this post, we showed how to use the Amazon Q Business browser extension to give your team seamless access to AI-driven insights and assistance. The browser extension is now available in US East (N. Virginia) and US West (Oregon) AWS Regions for Mozilla, Google Chrome, and Microsoft Edge as part of the Lite Subscription.  ( 41 min )
    Build Agentic Workflows with OpenAI GPT OSS on Amazon SageMaker AI and Amazon Bedrock AgentCore
    In this post, we show how to deploy gpt-oss-20b model to SageMaker managed endpoints and demonstrate a practical stock analyzer agent assistant example with LangGraph, a powerful graph-based framework that handles state management, coordinated workflows, and persistent memory systems.  ( 41 min )

  • Open

    Streamline access to ISO-rating content changes with Verisk rating insights and Amazon Bedrock
    In this post, we dive into how Verisk Rating Insights, powered by Amazon Bedrock, large language models (LLM), and Retrieval Augmented Generation (RAG), is transforming the way customers interact with and access ISO ERC changes.  ( 41 min )
    Unified multimodal access layer for Quora’s Poe using Amazon Bedrock
    In this post, we explore how the AWS Generative AI Innovation Center and Quora collaborated to build a unified wrapper API framework that dramatically accelerates the deployment of Amazon Bedrock FMs on Quora’s Poe system. We detail the technical architecture that bridges Poe’s event-driven ServerSentEvents protocol with Amazon Bedrock REST-based APIs, demonstrate how a template-based configuration system reduced deployment time from days to 15 minutes, and share implementation patterns for protocol translation, error handling, and multi-modal capabilities.  ( 47 min )

  • Open

    Schedule topology-aware workloads using Amazon SageMaker HyperPod task governance
    In this post, we introduce topology-aware scheduling with SageMaker HyperPod task governance by submitting jobs that represent hierarchical network information. We provide details about how to use SageMaker HyperPod task governance to optimize your job efficiency.  ( 37 min )
    How msg enhanced HR workforce transformation with Amazon Bedrock and msg.ProfileMap
    In this post, we share how msg automated data harmonization for msg.ProfileMap, using Amazon Bedrock to power its large language model (LLM)-driven data enrichment workflows, resulting in higher accuracy in HR concept matching, reduced manual workload, and improved alignment with compliance requirements under the EU AI Act and GDPR.  ( 36 min )
  • Open

    SRE Weekly Issue #494
    View on sreweekly.com SRE Weekly will be on hiatus for the next 6 weeks while I’m on medical leave. If all goes to plan, I’ll be donating a kidney for a loved one later this week, reducing my internal redundancy to help them respond to their own internal renal incident. If you’re interested, I invite […]  ( 4 min )

  • Open

    Automate advanced agentic RAG pipeline with Amazon SageMaker AI
    In this post, we walk through how to streamline your RAG development lifecycle from experimentation to automation, helping you operationalize your RAG solution for production deployments with Amazon SageMaker AI, helping your team experiment efficiently, collaborate effectively, and drive continuous improvement.  ( 45 min )
    Unlock model insights with log probability support for Amazon Bedrock Custom Model Import
    In this post, we explore how log probabilities work with imported models in Amazon Bedrock. You will learn what log probabilities are, how to enable them in your API calls, and how to interpret the returned data. We also highlight practical applications—from detecting potential hallucinations to optimizing RAG systems and evaluating fine-tuned models—that demonstrate how these insights can improve your AI applications, helping you build more trustworthy solutions with your custom models.  ( 45 min )
    Migrate from Anthropic’s Claude 3.5 Sonnet to Claude 4 Sonnet on Amazon Bedrock
    This post provides a systematic approach to migrating from Anthropic’s Claude 3.5 Sonnet to Claude 4 Sonnet on Amazon Bedrock. We examine the key model differences, highlight essential migration considerations, and deliver proven best practices to transform this necessary transition into a strategic advantage that drives measurable value for your organization.  ( 42 min )

  • Open

    Enhance video understanding with Amazon Bedrock Data Automation and open-set object detection
    In real-world video and image analysis, businesses often face the challenge of detecting objects that weren’t part of a model’s original training set. This becomes especially difficult in dynamic environments where new, unknown, or user-defined objects frequently appear. In this post, we explore how Amazon Bedrock Data Automation uses OSOD to enhance video understanding.  ( 17 min )
    How Skello uses Amazon Bedrock to query data in a multi-tenant environment while keeping logical boundaries
    Skello is a leading human resources (HR) software as a service (SaaS) solution focusing on employee scheduling and workforce management. Catering to diverse sectors such as hospitality, retail, healthcare, construction, and industry, Skello offers features including schedule creation, time tracking, and payroll preparation. We dive deep into the challenges of implementing large language models (LLMs) for data querying, particularly in the context of a French company operating under the General Data Protection Regulation (GDPR).  ( 20 min )
    Create a private workforce on Amazon SageMaker Ground Truth with the AWS CDK
    In this post, we present a complete solution for programmatically creating private workforces on Amazon SageMaker AI using the AWS Cloud Development Kit (AWS CDK), including the setup of a dedicated, fully configured Amazon Cognito user pool.  ( 20 min )

  • Open

    TII Falcon-H1 models now available on Amazon Bedrock Marketplace and Amazon SageMaker JumpStart
    We are excited to announce the availability of the Technology Innovation Institute (TII)’s Falcon-H1 models on Amazon Bedrock Marketplace and Amazon SageMaker JumpStart. With this launch, developers and data scientists can now use six instruction-tuned Falcon-H1 models (0.5B, 1.5B, 1.5B-Deep, 3B, 7B, and 34B) on AWS, and have access to a comprehensive suite of hybrid architecture models that combine traditional attention mechanisms with State Space Models (SSMs) to deliver exceptional performance with unprecedented efficiency.  ( 21 min )
    Oldcastle accelerates document processing with Amazon Bedrock
    This post explores how Oldcastle partnered with AWS to transform their document processing workflow using Amazon Bedrock with Amazon Textract. We discuss how Oldcastle overcame the limitations of their previous OCR solution to automate the processing of hundreds of thousands of POD documents each month, dramatically improving accuracy while reducing manual effort.  ( 16 min )
    How London Stock Exchange Group is detecting market abuse with their AI-powered Surveillance Guide on Amazon Bedrock
    In this post, we explore how London Stock Exchange Group (LSEG) used Amazon Bedrock and Anthropic's Claude foundation models to build an automated system that significantly improves the efficiency and accuracy of market surveillance operations.  ( 21 min )
    Build trustworthy AI agents with Amazon Bedrock AgentCore Observability
    In this post, we walk you through implementation options for both agents hosted on Amazon Bedrock AgentCore Runtime and agents hosted on other services like Amazon Elastic Compute Cloud (Amazon EC2), Amazon Elastic Kubernetes Service (Amazon EKS), AWS Lambda, or alternative cloud providers. We also share best practices for incorporating observability throughout the development lifecycle.  ( 21 min )

  • Open

    Powering innovation at scale: How AWS is tackling AI infrastructure challenges
    As generative AI continues to transform how enterprises operate—and develop net new innovations—the infrastructure demands for training and deploying AI models have grown exponentially. Traditional infrastructure approaches are struggling to keep pace with today’s computational requirements, network demands, and resilience needs of modern AI workloads. At AWS, we’re also seeing a transformation across the technology […]  ( 16 min )
    Accelerate your model training with managed tiered checkpointing on Amazon SageMaker HyperPod
    AWS announced managed tiered checkpointing in Amazon SageMaker HyperPod, a purpose-built infrastructure to scale and accelerate generative AI model development across thousands of AI accelerators. Managed tiered checkpointing uses CPU memory for high-performance checkpoint storage with automatic data replication across adjacent compute nodes for enhanced reliability. In this post, we dive deep into those concepts and understand how to use the managed tiered checkpointing feature.  ( 23 min )
2025-10-08T10:17:31.056Z osmosfeed 1.15.1