PDF.co Document Parser is an AI-powered tool for automating document parsing for automated extraction from invoices, orders, reports, PDF, scanned documents, and other business documents.

PDF.co Document Parser Key Features

Process PDF Invoices with PDF.co

  • Extracts data from PDF, images, scans, and documents
  • Built-in AI-powered templates and macros for rapid automated data extraction from invoices, reports, statements;
  • No programming is required to create or update data extraction templates. Maintenance and updates are easy with a Visual Template Editor;
  • CSV, XML, or JSON output;
  • Built-in OCR recognition (multiple languages) and AI-powered engine for increased data accuracy;
  • Built-in integration with 300+ leading online platforms.

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Document Parser Integrations

Document Parser Workflow

  • Use template editor to create document parser template;
  • Use PDF.co platform via API or via integrations (Zapier and others) and set the template ID for it;
  • Run PDF.co platform for automated data extraction from your documents and PDF.

Document Parser Template Editor screenshot

Document Parser template editor invoice

Our customers achieve up to x10 times faster time to market when needing to parse documents and are able to drastically decrease expenses for the implementation of high volumes of data extraction from orders, invoices, statements, and documents.

Document Parser engine can process high volumes of documents and files in the cloud. For sensitive documents, we also provide the on-premise version of Document Parser API that you can install and run on your own server and use your own private data storage, even without an Internet connection required.

Document Parser can extract invoice data from PDF in Python, C#, C++, Java, JavaScript, cURL, PHP, and any programming language you need.

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NOTE: Use PDF.co Document Classifier to automatically detect and sort documents by vendor automatically find a document type or document source. You can easily create and maintain classification rules with the desktop-based Classifier Testing Tool (see the details here)

 

Tutorials

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