In this post, we explore how natural language database analytics can revolutionize the way organizations interact with their structured data through the power of large language model (LLM) agents. Natural language interfaces to databases have long been a goal in data management. Agents enhance database analytics by breaking down complex queries into explicit, verifiable reasoning … Read more
Retrieval Augmented Generation (RAG) is a powerful approach for building generative AI applications by providing foundation models (FMs) access to additional, relevant data. This approach improves response accuracy and transparency while avoiding the potential cost and complexity of FM training or fine-tuning. Many customers use Amazon Bedrock Knowledge Bases to help implement RAG workflows. You … Read more
Intelligent document processing (IDP) refers to the automated extraction, classification, and processing of data from various document formats—both structured and unstructured. Within the IDP landscape, key information extraction (KIE) serves as a fundamental component, enabling systems to identify and extract critical data points from documents with minimal human intervention. Organizations across diverse sectors—including financial services, … Read more
Today, Amazon SageMaker HyperPod is announcing a new one-click, validated cluster creation experience that accelerates setup and prevents common misconfigurations, so you can launch your distributed training and inference clusters complete with Slurm or Amazon Elastic Kubernetes Service (Amazon EKS) orchestration, Amazon Virtual Private Cloud (Amazon VPC) networking, high-performance storage, and security built in by … Read more
This post was co-written with Nick Frichette and Vijay George from Datadog. As organizations increasingly adopt Amazon Bedrock for generative AI applications, protecting against misconfigurations that could lead to data leaks or unauthorized model access becomes critical. The AWS Generative AI Adoption Index, which surveyed 3,739 senior IT decision-makers across nine countries, revealed that 45% … Read more
When deploying AI agents to Amazon Bedrock AgentCore Runtime (currently in preview), customers often want to use custom domain names to create a professional and seamless experience. By default, AgentCore Runtime agents use endpoints like https://bedrock-agentcore.{region}.amazonaws.com/runtimes/{EncodedAgentARN}/invocations. In this post, we discuss how to transform these endpoints into user-friendly custom domains (like https://agent.yourcompany.com) using Amazon CloudFront … Read more
Today, we’re excited to announce that Amazon SageMaker HyperPod now supports managed node automatic scaling with Karpenter, so you can efficiently scale your SageMaker HyperPod clusters to meet your inference and training demands. Real-time inference workloads require automatic scaling to address unpredictable traffic patterns and maintain service level agreements (SLAs). As demand spikes, organizations must … Read more
This post is co-written with Julieta Rappan, Macarena Blasi, and María Candela Blanco from the Government of the City of Buenos Aires. The Government of the City of Buenos Aires continuously works to improve citizen services. In February 2019, it introduced an AI assistant named Boti available through WhatsApp, the most widely used messaging service … Read more
Air pollution remains one of Africa’s most pressing environmental health crises, causing widespread illness across the continent. Organizations like sensors.AFRICA have deployed hundreds of air quality sensors to address this challenge, but face a critical data problem: significant gaps in PM2.5 (particulate matter with diameter less than or equal to 2.5 micrometers) measurement records because … Read more
Finance analysts across Amazon Finance face mounting complexity in financial planning and analysis processes. When working with vast datasets spanning multiple systems, data lakes, and business units, analysts encounter several critical challenges. First, they spend significant time manually browsing data catalogs and reconciling data from disparate sources, leaving less time for valuable analysis and insight … Read more
Today, we are excited to announce that Mercury and Mercury Coder foundation models (FMs) from Inception Labs are available through Amazon Bedrock Marketplace and Amazon SageMaker JumpStart. With this launch, you can deploy the Mercury FMs to build, experiment, and responsibly scale your generative AI applications on AWS. In this post, we demonstrate how to … Read more
Healthcare discovery on ecommerce domains presents unique challenges that traditional product search wasn’t designed to handle. Unlike searching for books or electronics, healthcare queries involve complex relationships between symptoms, conditions, treatments, and services, requiring sophisticated understanding of medical terminology and customer intent. This challenge became particularly relevant for Amazon as we expanded beyond traditional ecommerce … Read more
As data becomes more abundant and information systems grow in complexity, stakeholders need solutions that reveal quality insights. Applying emerging technologies to the geospatial domain offers a unique opportunity to create transformative user experiences and intuitive workstreams for users and organizations to deliver on their missions and responsibilities. In this post, we explore how you … Read more
Most organizations evaluating foundation models limit their analysis to three primary dimensions: accuracy, latency, and cost. While these metrics provide a useful starting point, they represent an oversimplification of the complex interplay of factors that determine real-world model performance. Foundation models have revolutionized how enterprises develop generative AI applications, offering unprecedented capabilities in understanding and … Read more
Every day, organizations process millions of documents, including invoices, contracts, insurance claims, medical records, and financial statements. Despite the critical role these documents play, an estimated 80–90% of the data they contain is unstructured and largely untapped, hiding valuable insights that could transform business outcomes. Despite advances in technology, many organizations still rely on manual … Read more
Amazon SageMaker HyperPod is a purpose-built infrastructure for optimizing foundation model (FM) training and inference at scale. SageMaker HyperPod removes the undifferentiated heavy lifting involved in building and optimizing machine learning (ML) infrastructure for training FMs, reducing training time by up to 40%. SageMaker HyperPod offers persistent clusters with built-in resiliency, while also offering deep … Read more
This post is the second part of the GPT-OSS series focusing on model customization with Amazon SageMaker AI. In Part 1, we demonstrated fine-tuning GPT-OSS models using open source Hugging Face libraries with SageMaker training jobs, which supports distributed multi-GPU and multi-node configurations, so you can spin up high-performance clusters on demand. In this post, … Read more
Today, we are excited to announce the public preview of support for inline code nodes in Amazon Bedrock Flows. With this powerful new capability, you can write Python scripts directly within your workflow, alleviating the need for separate AWS Lambda functions for simple logic. This feature streamlines preprocessing and postprocessing tasks (like data normalization and … Read more
As an Amazon Web Services (AWS) enterprise customer, you’re probably exploring ways to use generative AI to enhance your business processes, improve customer experiences, and drive innovation. With a variety of options available—from Amazon Q Business to other AWS services or third-party offerings—choosing the right tool for your use case can be challenging. This post … Read more
Amazon SageMaker Unified Studio is a single integrated development environment (IDE) that brings together your data tools for analytics and AI. As part of the next generation of Amazon SageMaker, it contains integrated tooling for building data pipelines, sharing datasets, monitoring data governance, running SQL analytics, building artificial intelligence and machine learning (AI/ML) models, and … Read more
AI-powered apps and AI-powered service delivery are key differentiators in the enterprise space today. A generative AI-based resource can greatly reduce the onboarding time for new employees, enhance enterprise search, assist in drafting content, check for compliance, understand the legal language of data, and more. Generative AI applications are an emerging and sought-after solution in … Read more
This post was written with Jake Friedman from Wildlife. Businesses are seeking innovative ways to differentiate themselves through hyper-personalization and enhanced customer experiences. At the Cannes Lions International Festival of Creativity 2025, AWS showcased The Fragrance Lab, an interactive and inspiring experience that demonstrates how generative AI can support the development of hyper-personalized consumer goods … Read more
Tyson Foodservice operates as a critical division within Tyson Foods Inc., using its extensive protein production capabilities to supply a diverse array of foodservice clients across multiple sectors. As one of the largest protein providers in the US, Tyson Foods produces approximately 20% of the nation’s beef, pork, and chicken, which forms the foundation of … Read more
Machine learning (ML) has evolved from an experimental phase to becoming an integral part of business operations. Organizations now actively deploy ML models for precise sales forecasting, customer segmentation, and churn prediction. While traditional ML continues to transform business processes, generative AI has emerged as a revolutionary force, introducing powerful and accessible tools that reshape … Read more
AWS supports trusted identity propagation, a feature that allows AWS services to securely propagate a user’s identity across service boundaries. With trusted identity propagation, you have fine-grained access controls based on a physical user’s identity rather than relying on IAM roles. This integration allows for the implementation of access control through services such as Amazon … Read more
Every day, enterprises process thousands of documents containing critical business information. From invoices and purchase orders to forms and contracts, accurately locating and extracting specific fields has traditionally been one of the most complex challenges in document processing pipelines. Although optical character recognition (OCR) can tell us what text exists in a document, determining where … Read more
Enterprises across industries like healthcare, finance, manufacturing, and legal services face escalating challenges in processing vast amounts of multimodal data that combines text, images, charts, and complex technical formats. As organizations generate multimodal content at unprecedented speed and scale, document processing methods increasingly fail to handle the intricacies of specialized domains where technical terminology, interconnected … Read more
Amazon Q Business is a generative AI-powered assistant for interacting with organizational knowledge and enterprise systems. In addition to providing built-in connectors and plug-ins to connect seamlessly to over 40 popular enterprise systems, Amazon Q Business provides the ability to interact seamlessly with other third-party applications using custom plugins. Some of the enterprise systems that … Read more
Traveling is enjoyable, but travel planning can be complex to navigate and a hassle. Travelers must book accommodations, plan activities, and arrange local transportation. All these decisions can feel overwhelming. Although travel professionals have long helped manage these complexities, recent breakthroughs in generative AI have made something entirely new possible—intelligent assistants that can understand natural … Read more
To fulfill their tasks, AI Agents need access to various capabilities including tools, data stores, prompt templates, and other agents. As organizations scale their AI initiatives, they face an exponentially growing challenge of connecting each agent to multiple tools, creating an M×N integration problem that significantly slows development and increases complexity. Although protocols such as … Read more