Categorization IDP Machine Learning 
AWS Machine Learning Blog
MARCH 20, 2025
It often requires managing multiple machine learning (ML) models, designing complex workflows, and integrating diverse data sources into production-ready formats. IDP is powering critical workflows across industries and enabling businesses to scale with speed and accuracy. billion in 2025 to USD 66.68
AWS Machine Learning Blog
NOVEMBER 22, 2023
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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MARCH 22, 2023
Snowflake is an AWS Partner with multiple AWS accreditations, including AWS competencies in machine learning (ML), retail, and data and analytics. 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. Configure Snowflake.
AWS Machine Learning Blog
JUNE 18, 2024
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. There may occasionally be different sorts of documents and no automatic method for identifying and categorizing them.
AWS Machine Learning Blog
APRIL 11, 2024
Organizations across industries want to categorize and extract insights from high volumes of documents of different formats. Categorizing documents is an important first step in IDP systems. For optimal performance, you should customize the solution to your specific use case and existing IDP pipeline setup.
AWS Machine Learning Blog
OCTOBER 24, 2023
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.
AWS Machine Learning Blog
FEBRUARY 21, 2025
Rule-based systems or specialized machine learning (ML) models often struggle with the variability of real-world documents, especially when dealing with semi-structured and unstructured data. We demonstrate how generative AI along with external tool use offers a more flexible and adaptable solution to this challenge.
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