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Build well-architected IDP solutions with a custom lens – Part 1: Operational excellence

AWS Machine Learning Blog

The IDP Well-Architected Lens is intended for all AWS customers who use AWS to run intelligent document processing (IDP) solutions and are searching for guidance on how to build secure, efficient, and reliable IDP solutions on AWS. This post focuses on the Operational Excellence pillar of the IDP solution.

IDP 100
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Orchestrate an intelligent document processing workflow using tools in Amazon Bedrock

AWS Machine Learning Blog

Generative AI is revolutionizing enterprise automation, enabling AI systems to understand context, make decisions, and act independently. At AWS, were using the power of models in Amazon Bedrock to drive automation of complex processes that have traditionally been challenging to streamline. with the guardrail ID you created in Step 3.

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Implement smart document search index with Amazon Textract and Amazon OpenSearch

AWS Machine Learning Blog

The implementation used in this post utilizes the Amazon Textract IDP CDK constructs – AWS Cloud Development Kit (CDK) components to define infrastructure for Intelligent Document Processing (IDP) workflows – which allow you to build use case specific customizable IDP workflows. Testing First test using a sample file.

IDP 120
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Build a receipt and invoice processing pipeline with Amazon Textract

AWS Machine Learning Blog

In this post, we show how to automate the accounts payable process using Amazon Textract for data extraction. We also provide a reference architecture to build an invoice automation pipeline that enables extraction, verification, archival, and intelligent search. Name==`InvoiceProcessorWorkflow-CognitoUserPoolId`].Value'

IDP 107
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Using natural language in Amazon Q Business: From searching and creating ServiceNow incidents and knowledge articles to generating insights

AWS Machine Learning Blog

When you use identity federation, you can manage users with your enterprise identity provider (IdP) and use IAM to authenticate users when they sign in to Amazon Q Business. Therefore, the OpenAPI schema definition has a big impact on API selection accuracy and might require design optimizations.

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Multilingual content processing using Amazon Bedrock and Amazon A2I

AWS Machine Learning Blog

The global intelligent document processing (IDP) market size was valued at $1,285 million in 2022 and is projected to reach $7,874 million by 2028 ( source ). Extraction – A document schema definition is used to formulate the prompt and documents are embedded into the prompt and sent to Amazon Bedrock for extraction.

IDP 90
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Automate document processing with Amazon Bedrock Prompt Flows (preview)

AWS Machine Learning Blog

However, the rise of intelligent document processing (IDP), which uses the power of artificial intelligence and machine learning (AI/ML) to automate the extraction, classification, and analysis of data from various document types is transforming the game. Results of the extraction and analysis are stored in Amazon S3. json ├── pages_0.txt