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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

Amazon Bedrock offers a serverless experience so you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using AWS tools without having to manage infrastructure.

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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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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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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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Build an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and AWS CloudFormation

AWS Machine Learning - AI

Prerequisites To implement the solution provided in this post, you should have the following: An active AWS account and familiarity with FMs, Amazon Bedrock, and OpenSearch Serverless. An S3 bucket where your documents are stored in a supported format (.txt,md,html,doc/docx,csv,xls/.xlsx,pdf). txt,md,html,doc/docx,csv,xls/.xlsx,pdf).

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Build an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and the AWS CDK

AWS Machine Learning - AI

By using the AWS CDK, the solution sets up the necessary resources, including an AWS Identity and Access Management (IAM) role, Amazon OpenSearch Serverless collection and index, and knowledge base with its associated data source. An S3 bucket set up with your documents in a supported format (.txt,md,html,doc/docx,csv,xls/.xlsx,pdf).

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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. Recommend AWS best practices for system design with the AWS Well-Architected Framework guidelines. Create, associate, and ingest data into the two knowledge bases.