Remove IDP Remove Large Language Models Remove Metadata
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Build private and secure enterprise generative AI applications with Amazon Q Business using IAM Federation

AWS Machine Learning Blog

If you want to use Amazon Q Business to build enterprise generative AI applications, and have yet to adopt organization-wide use of AWS IAM Identity Center , you can use Amazon Q Business IAM Federation to directly manage user access to Amazon Q Business applications from your enterprise identity provider (IdP), such as Okta or Ping Identity.

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Intelligent document processing with Amazon Textract, Amazon Bedrock, and LangChain

AWS Machine Learning Blog

Document processing has witnessed significant advancements with the advent of Intelligent Document Processing (IDP). With IDP, businesses can transform unstructured data from various document types into structured, actionable insights, dramatically enhancing efficiency and reducing manual efforts.

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Discover insights from Amazon S3 with Amazon Q S3 connector 

AWS Machine Learning Blog

Next you need to index the data to make it available for a Retrieval Augmented Generation (RAG) approach where relevant passages are delivered with high accuracy to a large language model (LLM). The user’s credentials from the IdP or IAM Identity Center are referred to here as the federated user credentials.

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Find answers accurately and quickly using Amazon Q Business with the SharePoint Online connector

AWS Machine Learning Blog

This enables the Amazon Q large language model (LLM) to provide accurate, well-written answers by drawing from the consolidated data and information. The SharePoint online data source can be optionally connected to an IdP such as Okta or Microsoft Entra ID.

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Create a document lake using large-scale text extraction from documents with Amazon Textract

AWS Machine Learning Blog

However, they’re unable to gain insights such as using the information locked in the documents for large language models (LLMs) or search until they extract the text, forms, tables, and other structured data. We use the IDP AWS CDK constructs , which make it straightforward to work with Amazon Textract at scale.

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Dialogue-guided intelligent document processing with foundation models on Amazon SageMaker JumpStart

AWS Machine Learning Blog

Intelligent document processing (IDP) is a technology that automates the processing of high volumes of unstructured data, including text, images, and videos. Natural language processing (NLP) is one of the recent developments in IDP that has improved accuracy and user experience.

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Discover insights from Box with the Amazon Q Box connector

AWS Machine Learning Blog

Next, you need to index this data to make it available for a Retrieval Augmented Generation (RAG) approach where relevant passages are delivered with high accuracy to a large language model (LLM). Amazon Q supports the crawling and indexing of these custom objects and custom metadata.

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