Items tagged with “Amazon”.
A detailed look at how Amazon Bedrock AgentCore helps transition agent-based AI applications from experimental proof of concept to enterprise-grade production systems, preserving security, memory, observability, and scalable tool management.
Amazon Bedrock now offers Stability AI Image Services, extending Stable Diffusion and Stable Image with nine tools for precise image creation and editing. Learn prompting best practices for enterprise use.
Learn how to monitor and optimize Amazon Bedrock batch inference jobs with CloudWatch metrics, alarms, and dashboards to improve performance, cost efficiency, and operational oversight.
Stability AI Image Services are now available in Amazon Bedrock, delivering ready-to-use media editing via the Bedrock API and expanding on Stable Diffusion models already in Bedrock.
Explore how AWS Deep Learning Containers (DLCs) integrate with SageMaker AI managed MLflow to balance infrastructure control and robust ML governance. A TensorFlow abalone age prediction workflow demonstrates end-to-end tracking, model governance, and deployment traceability.
An end-to-end look at deploying OpenAI GPT OSS models on SageMaker AI and Bedrock AgentCore to power a multi-agent stock analyzer with LangGraph, including 4-bit MXFP4 quantization, serverless orchestration, and scalable inference.
The Amazon Q Business browser extension brings context-aware, AI-driven assistance to your browser for Lite and Pro subscribers, enabling rapid, source-backed insights and seamless workflows.
Verisk Rating Insights, powered by Amazon Bedrock, LLMs, and RAG, enables a conversational interface to access ISO ERC changes, reducing manual downloads and enabling faster, accurate insights.
AWS and Quora introduce a unified wrapper API to accelerate deploying Amazon Bedrock foundation models on Poe, bridging Poe's ServerSentEvents with Bedrock REST APIs and enabling rapid, scalable multi-modal AI deployments.
This post explains how msg automated data harmonization for msg.ProfileMap using Amazon Bedrock to power LLM-driven data enrichment, boosting HR concept matching accuracy, reducing manual workload, and aligning with EU AI Act and GDPR.
AWS introduces topology-aware scheduling with SageMaker HyperPod task governance to optimize training efficiency and network latency on EKS clusters, using EC2 topology data to guide job placement.
Streamline experimentation to production for Retrieval Augmented Generation (RAG) with SageMaker AI, MLflow, and Pipelines, enabling reproducible, scalable, and governance-ready workflows.
A structured guide to migrating from Anthropic Claude 3.5 Sonnet to Claude 4 Sonnet on Amazon Bedrock, covering model differences, access, APIs, extended thinking, evaluation, and rollout best practices.
Explains token-level confidence data for imported Bedrock models via log probabilities, how to enable, and practical use cases for reliability.
Automate the creation of private workforces for SageMaker Ground Truth with a dedicated Cognito user pool using the AWS CDK. This article covers the architecture, implementation details, and migration considerations for IaC-driven private labeling workflows.
Open-set object detection (OSOD) enables recognizing known and unseen objects in video. This article explains how Amazon Bedrock Data Automation uses OSOD on frame-level video analysis to deliver flexible, prompt-driven object detection without retraining.
Skello implements an AI-powered assistant on AWS Bedrock and Lambda to enable natural-language queries across a multi-tenant HR platform, while enforcing GDPR-compliant data boundaries, standardized data models, and robust security.
LSEG uses Amazon Bedrock and Anthropic's Claude to automate market surveillance, analyzing 250,000 RNS articles from 2023 to assess price sensitivity and reduce false positives, boosting efficiency and accuracy.
This article explains how Oldcastle APG partnered with AWS to automate hundreds of thousands of proof-of-delivery documents each month using Amazon Bedrock with Amazon Textract, replacing unreliable OCR and reducing manual effort.
AWS announces the Falcon-H1 instruction-tuned models from TII (0.5B–34B) on Amazon Bedrock Marketplace and SageMaker JumpStart, with multilingual support, a hybrid architecture, and deployment guidance.
A detailed look at using the HyperPod CLI and SDK to streamline training and deploying large AI models on SageMaker HyperPod, with practical steps for FSDP-based training and inference deployment.
SageMaker HyperPod introduces a one-click, validated cluster creation experience that automatically provisions prerequisite resources and prescriptive defaults, accelerating distributed training and inference with Slurm or EKS orchestration.
A scalable, serverless workflow for Bedrock batch inference orchestrated by AWS Step Functions. Demonstrated on a 2.2 million-row dataset with preprocessing, parallel execution, and postprocessing.
Automate deploying Amazon Bedrock knowledge bases and data-source connections for RAG workflows with a Terraform IaC template, enabling rapid, reproducible setups for production systems.
End-to-end KIE solution approach using Amazon Nova models via Amazon Bedrock; FATURA dataset; model-agnostic prompts; evaluation with F1-score to balance accuracy, speed, and cost.
Explores natural language database analytics using Amazon Nova foundation models, ReAct reasoning, and LangGraph to translate natural language queries into accurate SQL, enabling HITL-guided, self-healing data analysis.
SageMaker HyperPod now offers managed node automatic scaling powered by Karpenter, enabling responsive, cost-aware scaling for inference and training workloads on HyperPod clusters.
Datadog Cloud Security now includes detections and remediation guidance to spot and fix Amazon Bedrock misconfigurations, helping secure AI workloads and align with evolving regulations.
Learn how to transform Amazon Bedrock AgentCore Runtime endpoints into user-friendly custom domains using CloudFront, Route 53, and ACM. This approach streamlines integration, aligns domains with organizations, and enables secure, scalable access.
Demonstrates a data imputation solution for PM2.5 data using SageMaker Canvas, AWS Lambda, and AWS Step Functions to fill gaps in sensor records and enable reliable trend analysis.
Amazon Finance details an AI-powered assistant that blends Bedrock and Kendra to accelerate data discovery, preserve institutional knowledge, and deliver accurate financial insights at scale.
A new agentic AI assistant for Buenos Aires, built with LangGraph and Amazon Bedrock, uses guardrails and a reasoning retrieval system to answer citizens’ questions about government procedures while ensuring safe, accurate responses.
AWS announces Mercury and Mercury Coder foundation models from Inception Labs are now accessible via Amazon Bedrock Marketplace and SageMaker JumpStart, enabling ultra-fast diffusion-based generation for AWS generative AI workloads.
A detailed look at how Amazon Health Services improved search discoverability on Amazon.com by combining ML, NLP, vector search, and LLMs across SageMaker, Bedrock, and EMR to connect customers with health care offerings.
Open source GenAI IDP Accelerator combines generative AI with AWS Bedrock to automate, scale, and reduce manual effort in processing diverse documents across industries.
A methodical approach for choosing foundation models in Amazon Bedrock, balancing task performance, architecture, operations, and responsible AI to align with business goals and user needs.
SageMaker HyperPod adds continuous provisioning and custom AMIs to deliver flexible resource provisioning, security-aligned environments, and enterprise-grade control for large-scale foundation model training and inference on EKS.
This article outlines a systematic evaluation framework for choosing foundation models in Amazon Bedrock, combining theory with practical steps to balance performance, cost, and operational needs.
Explores how to integrate geospatial data and GIS workflows with Amazon Bedrock, leveraging LLMs, RAG, and Bedrock Agents to unlock insights and streamline operations.
AWS customers can deploy Amazon Q Business to streamline knowledge access, automate workflows, and strengthen security across enterprise data, with guided architecture and phased deployment.
A detailed look at fine-tuning GPT-OSS models with SageMaker HyperPod recipes and training jobs, including multilingual data, deployment, and practical steps for enterprise-grade training.
Infosys Topaz integrates Amazon Bedrock to power an AI-driven technical help desk for a large energy supplier, ingesting transcripts, building a knowledge base, and delivering faster, contextual support with strong security and RBAC.
Public preview enables Python inline code nodes in Bedrock Flows, letting you run small scripts inside workflows without separate Lambda functions, accelerating AI workflow development.
Learn how Code Editor and multiple spaces in Amazon SageMaker Unified Studio accelerate end-to-end ML workflows, from development to training, evaluation, and optional deployment.
An end-to-end demonstration of hyper-personalized consumer goods and advertising campaigns built with Amazon Nova in Bedrock, showcased at Cannes Lions 2025 and backed by Guardrails, RAG, and on-site perfumers.
A detailed look at extending AI agents with predictive ML models hosted on Amazon SageMaker AI, using the Model Context Protocol (MCP) and the Strands Agents SDK for scalable, secure tool integration.
In this post, we explore how Tyson Foods collaborated with the AWS Generative AI Innovation Center to revolutionize their customer interaction through an intuitive AI assistant integrated into their website. The AI assistant was built using Amazon Bedrock,
A benchmarking study shows how Amazon Nova Pro on Bedrock enables high-accuracy document field localization using multimodal models, with FATURA benchmarking and practical implementation guidance.
We built an advanced RAG solution using Amazon Bedrock leveraging Infosys Topaz™ AI capabilities, tailored for the oil and gas sector. This solution excels in handling multimodal data sources, seamlessly processing text, diagrams, and numerical data while maintaining context and relationships betwee
In this post, we explore how to enable and use trusted identity propagation in Amazon SageMaker Studio, which allows organizations to simplify access management by granting permissions to existing AWS IAM Identity Center identities. The solution demonstrates how to implement fine-grained access cont
In this post, we explore how to design and implement custom plugins for Amazon Q Business to create an intelligent chatbot that streamlines employee training by retrieving answers from training materials. The solution implements secure API access using Amazon Cognito for user authentication and auth
Learn how AWS used Amazon Nova and LangGraph to build a serverless, agent-based travel planning assistant with a three-layer architecture, function calling nodes, and extensible integrations.
Salesforce and AWS collaborated to optimize GPU utilization, boost resource efficiency, and cut costs by deploying multiple foundation models on SageMaker AI endpoints using inference components. This approach enables granular per-model resource control and dynamic scaling.
Amazon Q Business integrates Agentic Retrieval Augmented Generation (RAG) to transform enterprise data interaction with decomposed queries, real-time processing visibility, and memory-enabled conversations, grounded in enterprise data with clear citations.
Demonstrates prompting Amazon Nova understanding models to cite sources and how to evaluate responses for accuracy, using Nova Pro as an example.
Overview of how Amazon Bedrock Data Automation enhances IDP with confidence scoring, blueprints, and human-in-the-loop review for scalable, accurate document processing.
Explore how Amazon Bedrock AgentCore Memory enables AI agents to maintain short-term and long-term knowledge, transforming one-off conversations into continuous, evolving user interactions.
PwC and AWS integrate Automated Reasoning with Bedrock Guardrails to validate AI outputs against policy rules, enabling auditable compliance, faster safe innovation, and new industry use cases.
A deep dive into how Amazon Bedrock AgentCore Runtime enables secure, framework- and model-agnostic hosting for AI agents, with persistent session execution, microVM isolation, and scalable management for production deployments.