Generative AI

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Detect Amazon Bedrock misconfigurations with Datadog Cloud Security

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% […]

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Meet Boti: The AI assistant transforming how the citizens of Buenos Aires access government information with Amazon Bedrock

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

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Accelerate intelligent document processing with generative AI on AWS

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

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Beyond the basics: A comprehensive foundation model selection framework for generative AI

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

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Accelerate enterprise AI implementations with Amazon Q Business

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

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Create personalized products and marketing campaigns using Amazon Nova in Amazon Bedrock

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

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Enhance AI agents using predictive ML models with Amazon SageMaker AI and Model Context Protocol (MCP)

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

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How Infosys built a generative AI solution to process oil and gas drilling data with Amazon Bedrock

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

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Benchmarking document information localization with Amazon Nova

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

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Create a travel planning agentic workflow with Amazon Nova

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

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