AWS Machine Learning Blog

FEBRUARY 21, 2025

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.

Categorization 81

Categorization IDP Generative AI Automation 81

ODSC - Open Data Science

OCTOBER 27, 2023

These documents often contain vital information that drives timely decision-making, essential for ensuring top-tier customer satisfaction, and reduced customer churn. Traditionally, the extraction of data from documents is manual, making it slow, prone to errors, costly, and challenging to scale.

IDP 98

IDP LLM Large Language Models Data Science 98

AWS Machine Learning Blog

JUNE 26, 2024

Intelligent document processing (IDP) applies AI/ML techniques to automate data extraction from documents. Using IDP can reduce or eliminate the requirement for time-consuming human reviews. IDP has the power to transform the way capital market back-office operations work.

Automation 103

Automation IDP ML AI 103

Topbots

APRIL 4, 2024

By leveraging AI, organizations can automate the extraction and interpretation of information from documents to focus more on their core activities. Businesses can’t afford to wait days for document processing; they need information at their fingertips. IDP steps up the game. LLMs are like language wizards.

Automation 59

Automation IDP NLP Natural Language Processing 59

AWS Machine Learning Blog

MAY 24, 2023

Fraudulent paperwork includes but is not limited to altering or falsifying paystubs, inflating information about income, misrepresenting job status, and forging letters of employment and other key mortgage underwriting documents. This helps identify top risk indicators and analyze fraud patterns across the data.

Automation 79

Automation Computer Vision Data Extraction IDP 79

AWS Machine Learning Blog

JUNE 12, 2024

In today’s data-driven business landscape, the ability to efficiently extract and process information from a wide range of documents is crucial for informed decision-making and maintaining a competitive edge. The following screenshot shows the updated information on the Private tab.

IDP 121

IDP NLP Natural Language Processing Generative AI 121

AWS Machine Learning Blog

MARCH 29, 2023

In this post, we discuss how the IEO developed UNDP’s artificial intelligence and machine learning (ML) platform—named Artificial Intelligence for Development Analytics (AIDA)— in collaboration with AWS, UNDP’s Information and Technology Management Team (UNDP ITM), and the United Nations International Computing Centre (UNICC).

ML 79

ML Metadata Data Ingestion Data Extraction 79

AWS Machine Learning Blog

NOVEMBER 13, 2024

The market size for multilingual content extraction and the gathering of relevant insights from unstructured documents (such as images, forms, and receipts) for information processing is rapidly increasing. In this stage, we store initial document information in an Amazon DynamoDB table after receiving an Amazon S3 event notification.

IDP 90

IDP Machine Learning Python ML 90

AWS Machine Learning Blog

OCTOBER 23, 2024

Automate intelligent document processing (IDP) – Agent Creator can extract valuable data from invoices, purchase orders, resumes, insurance claims, loan applications, and other unstructured sources automatically. This data was then integrated into Salesforce as a real-time feed of market insights.

Generative AI 73

Generative AI IDP LLM Automation 73

AWS Machine Learning Blog

JULY 18, 2024

Enterprise customers can unlock significant value by harnessing the power of intelligent document processing (IDP) augmented with generative AI. By infusing IDP solutions with generative AI capabilities, organizations can revolutionize their document processing workflows, achieving exceptional levels of automation and reliability.

IDP 123

IDP Generative AI Data Extraction Automation 123

AWS Machine Learning Blog

DECEMBER 17, 2024

Developers face significant challenges when using foundation models (FMs) to extract data from unstructured assets. This data extraction process requires carefully identifying models that meet the developers specific accuracy, cost, and feature requirements.

Automation 102

Automation IDP Generative AI Data Extraction 102