Remove Categorization Remove IDP Remove Information
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Unleashing the multimodal power of Amazon Bedrock Data Automation to transform unstructured data into actionable insights

AWS Machine Learning Blog

In a world whereaccording to Gartner over 80% of enterprise data is unstructured, enterprises need a better way to extract meaningful information to fuel innovation. IDP is powering critical workflows across industries and enabling businesses to scale with speed and accuracy. billion in 2025 to USD 66.68

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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. It also provides guidance to tackle common challenges, enabling you to architect your IDP workloads according to best practices.

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Access Snowflake data using OAuth-based authentication in Amazon SageMaker Data Wrangler

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With this new feature, you can use your own identity provider (IdP) such as Okta , Azure AD , or Ping Federate to connect to Snowflake via Data Wrangler. Solution overview In the following sections, we provide steps for an administrator to set up the IdP, Snowflake, and Studio. Provide the users within the IdP access to Data Wrangler.

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Streamline financial workflows with generative AI for email automation

AWS Machine Learning Blog

This represents a major opportunity for businesses to optimize this workflow, save time and money, and improve accuracy by modernizing antiquated manual document handling with intelligent document processing (IDP) on AWS. Finding relevant information that is necessary for business decisions is difficult.

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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.

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Orchestrate an intelligent document processing workflow using tools in Amazon Bedrock

AWS Machine Learning Blog

Through a practical use case of processing a patient health package at a doctors office, you will see how this technology can extract and synthesize information from all three document types, potentially improving data accuracy and operational efficiency. For more information, see Create a guardrail.

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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. Document processing has witnessed significant advancements with the advent of Intelligent Document Processing (IDP). However, the potential doesn’t end there.

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