PDF Parser

PDF Parser is an AI-powered tool designed to extract structured data from PDFs and images, targeting users who need to automate data entry from documents such as invoices, receipts, bank statements, contracts, insurance claims, medical records, and HR documents. The service enables users to upload files—supporting formats like PDF, JPEG, PNG, WebP, TIFF, BMP, and GIF—define custom fields with specific data types, and receive structured outputs in JSON or CSV format. Its AI engine, based on GPT-4-class vision models, performs context-aware extraction, handling both structured forms and unstructured free-text layouts without requiring templates or manual rule configuration.

The platform is accessible via a web interface that allows drag-and-drop uploads, batch processing, and live previews of extracted data. Users can specify field names, data types such as string, number, date, or boolean, and descriptions for each field. The system processes multiple documents simultaneously using a parallel processing engine, with processing times typically under 30 seconds per file and a maximum file size of 20 MB. For developers and integration into workflows, PDF Parser offers a REST API with full documentation, JSON Schema validation, and webhook notifications. All plans provide API access, and output can be directly integrated into spreadsheets, databases, or other systems.

Security is emphasized through the use of HTTPS encryption for all file transfers, and documents are not stored after processing is complete. Document processing leverages OpenAI’s API, which does not use customer data for model training. The service is available through subscription plans: Starter ($9/month for 100 pages), Pro ($29/month for 500 pages, with additional features like priority queue and chat support), and Business ($99/month for 2,500 pages, unlimited API access, and dedicated support). A free trial is offered, allowing up to 20 pages to be processed without a credit card. All plans renew monthly and can be cancelled at any time.