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Automate document processing with Amazon Bedrock Prompt Flows (preview)

AWS Machine Learning Blog

Enterprises in industries like manufacturing, finance, and healthcare are inundated with a constant flow of documents—from financial reports and contracts to patient records and supply chain documents. And in healthcare, IDP revolutionizes patient onboarding, claims processing, and medical record keeping.

IDP 108
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Build well-architected IDP solutions with a custom lens – Part 6: Sustainability

AWS Machine Learning Blog

An intelligent document processing (IDP) project typically combines optical character recognition (OCR) and natural language processing (NLP) to automatically read and understand documents. This post focuses on the Sustainability pillar of the IDP custom lens.

IDP 114
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Enhancing AWS intelligent document processing with generative AI

AWS Machine Learning Blog

Data classification, extraction, and analysis can be challenging for organizations that deal with volumes of documents. Traditional document processing solutions are manual, expensive, error prone, and difficult to scale. Generative AI is driven by large ML models called foundation models (FMs).

IDP 88
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Streamline financial workflows with generative AI for email automation

AWS Machine Learning Blog

Many companies across all industries still rely on laborious, error-prone, manual procedures to handle documents, especially those that are sent to them by email. Intelligent automation presents a chance to revolutionize document workflows across sectors through digitization and process optimization.

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Build well-architected IDP solutions with a custom lens – Part 5: Cost optimization

AWS Machine Learning Blog

An intelligent document processing (IDP) project usually combines optical character recognition (OCR) and natural language processing (NLP) to read and understand a document and extract specific terms or words. This post focuses on the Cost Optimization pillar of the IDP solution.

IDP 106
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Intelligent document processing with Amazon Textract, Amazon Bedrock, and LangChain

AWS Machine Learning Blog

In today’s information age, the vast volumes of data housed in countless documents present both a challenge and an opportunity for businesses. Traditional document processing methods often fall short in efficiency and accuracy, leaving room for innovation, cost-efficiency, and optimizations. However, the potential doesn’t end there.

IDP 134
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Cost-effective document classification using the Amazon Titan Multimodal Embeddings Model

AWS Machine Learning Blog

Organizations across industries want to categorize and extract insights from high volumes of documents of different formats. Manually processing these documents to classify and extract information remains expensive, error prone, and difficult to scale. Categorizing documents is an important first step in IDP systems.

IDP 124