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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. For instance, consider an AI-driven legal document analysis system designed for businesses of varying sizes, offering two primary subscription tiers: Basic and Pro.

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Track, allocate, and manage your generative AI cost and usage with Amazon Bedrock

AWS Machine Learning - AI

As enterprises increasingly embrace generative AI , they face challenges in managing the associated costs. With demand for generative AI applications surging across projects and multiple lines of business, accurately allocating and tracking spend becomes more complex.

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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. Users can access these AI capabilities through their organizations single sign-on (SSO), collaborate with team members, and refine AI applications without needing AWS Management Console access.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

While organizations continue to discover the powerful applications of generative AI , adoption is often slowed down by team silos and bespoke workflows. To move faster, enterprises need robust operating models and a holistic approach that simplifies the generative AI lifecycle.

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Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning - AI

Recently, we’ve been witnessing the rapid development and evolution of generative AI applications, with observability and evaluation emerging as critical aspects for developers, data scientists, and stakeholders. In the context of Amazon Bedrock , observability and evaluation become even more crucial.

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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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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

This engine uses artificial intelligence (AI) and machine learning (ML) services and generative AI on AWS to extract transcripts, produce a summary, and provide a sentiment for the call. Many commercial generative AI solutions available are expensive and require user-based licenses.