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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more crucial, offering deeper insights and strategic value to help organizations optimize their growing cloud environments. In this post, we explore a generative AI solution leveraging Amazon Bedrock to streamline the WAFR process.

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Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion

AWS Machine Learning - AI

Verisk (Nasdaq: VRSK) is a leading strategic data analytics and technology partner to the global insurance industry, empowering clients to strengthen operating efficiency, improve underwriting and claims outcomes, combat fraud, and make informed decisions about global risks. The user can pick the two documents that they want to compare.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

For example, consider a text summarization AI assistant intended for academic research and literature review. For instance, consider an AI-driven legal document analysis system designed for businesses of varying sizes, offering two primary subscription tiers: Basic and Pro. This is illustrated in the following figure.

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Revolutionizing clinical trials with the power of voice and AI

AWS Machine Learning - AI

This is where the integration of cutting-edge technologies, such as audio-to-text translation and large language models (LLMs), holds the potential to revolutionize the way patients receive, process, and act on vital medical information. Extraction of relevant data points for electronic health records (EHRs) and clinical trial databases.

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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

They have structured data such as sales transactions and revenue metrics stored in databases, alongside unstructured data such as customer reviews and marketing reports collected from various channels. The system will take a few minutes to set up your project. On the next screen, leave all settings at their default values.

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Create generative AI agents that interact with your companies’ systems in a few clicks using Amazon Bedrock in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

Companies of all sizes face mounting pressure to operate efficiently as they manage growing volumes of data, systems, and customer interactions. The chat agent bridges complex information systems and user-friendly communication. Update the due date for a JIRA ticket. List recent customer interactions.

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Automate Amazon Bedrock batch inference: Building a scalable and efficient pipeline

AWS Machine Learning - AI

To address this consideration and enhance your use of batch inference, we’ve developed a scalable solution using AWS Lambda and Amazon DynamoDB. This post guides you through implementing a queue management system that automatically monitors available job slots and submits new jobs as slots become available. Choose Submit.