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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

For instance, consider an AI-driven legal document analysis system designed for businesses of varying sizes, offering two primary subscription tiers: Basic and Pro. Meanwhile, the business analysis interface would focus on text summarization for analyzing various business documents.

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Automate emails for task management using Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, and Amazon Bedrock Guardrails

AWS Machine Learning - AI

Organizations possess extensive repositories of digital documents and data that may remain underutilized due to their unstructured and dispersed nature. Solution overview This section outlines the architecture designed for an email support system using generative AI.

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Knowledge Bases for Amazon Bedrock now supports advanced parsing, chunking, and query reformulation giving greater control of accuracy in RAG based applications

AWS Machine Learning - AI

However, it’s important to note that in RAG-based applications, when dealing with large or complex input text documents, such as PDFs or.txt files, querying the indexes might yield subpar results. Advanced parsing Advanced parsing is the process of analyzing and extracting meaningful information from unstructured or semi-structured documents.

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Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval

AWS Machine Learning - AI

For example, consider how the following source document chunk from the Amazon 2023 letter to shareholders can be converted to question-answering ground truth. To convert the source document excerpt into ground truth, we provide a base LLM prompt template. Further, Amazons operating income and Free Cash Flow (FCF) dramatically improved.

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

AWS Machine Learning - AI

Mozart, the leading platform for creating and updating insurance forms, enables customers to organize, author, and file forms seamlessly, while its companion uses generative AI to compare policy documents and provide summaries of changes in minutes, cutting the change adoption time from days or weeks to minutes.

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Medical content creation in the age of generative AI

AWS Machine Learning - AI

The solution has been designed using the following services: Amazon Elastic Container Service (ECS) : to deploy and manage our Streamlit UI. Amazon Lambda : to run the backend code, which encompasses the generative logic. Amazon Textract : for documents parsing, text, and layout extraction.

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Create a generative AI-based application builder assistant using Amazon Bedrock Agents

AWS Machine Learning - AI

The agent can recommend software and architecture design best practices using the AWS Well-Architected Framework for the overall system design. Create and associate an action group with an API schema and a Lambda function. Recommend AWS best practices for system design with the AWS Well-Architected Framework guidelines.