PDF Extract API Unlock the structure and content elements of any PDF by machine learning.

Introduction

PDFs are a common storage format for textual information. While many Python libraries can extract text from PDFs, our solution goes beyond mere text extraction. We aim to provide structured data extraction, including paragraphs, tables, images, charts, and other structured content. Our goal is to deliver structured data, not just plain text. Explore our solution to unlock the full potential of PDF data.

Unlock Document Structure with Precision

The PDF Extract API leverages cutting-edge Artificial Intelligence (AI) and Machine Learning (ML) technologies to provide deep insights into document structure. This includes precise element identification, positional relationships between elements, connections relative to other elements, and the order of content for effortless comprehension.

Two Primary Components:

Layout Understanding: This segment of the model is trained to recognize and interpret the layout of the document. It identifies elements like tables, figures, and text blocks, understanding how they are arranged and related to each other.

Textual Understanding: Once the layout is understood, this part delves into the textual content of the document. It applies advanced natural language processing techniques to comprehend the text and is capable of answering questions based on this understanding.

Get started in minutes

1. Click the link below to access the API interface description and view examples.

   PDF Scan API

2. If you're interested in our interface, please feel free to get in touch with us to request the access key.

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References Paper And Repo

1. PDFTriage: Question Answering over Long, Structured Documents

   arxiv papertwitter blogGithub Repo