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Product information: Parsebridge is a PDF parsing API that transforms PDFs into clean, structured Markdown. It extracts text, tables, and data from PDF documents with a powerful API built for developers who need reliable document parsing at scale. Complex PDFs, tables, multi-column layouts, nested structures, and scanned pages are handled in one API call, turning the hard parts that usually break other parsers into Markdown you can actually use. Merged cells, nested headers, and complex layouts are parsed correctly instead of coming back garbled. Parsebridge supports live testing by pasting a PDF URL or uploading a PDF to the preview page-one Markdown without an account. It currently supports PDF files only, focusing on extraction quality for PDF documents, with files up to 100MB supported. Under the hood, Parsebridge uses Docling, an open source parser known for table extraction and layout preservation, while the platform handles infrastructure, OCR, scaling, and the API layer on top.

Box Extract is an AI-powered data extraction solution that intelligently identifies, retrieves, and converts structured information from unstructured content such as documents, spreadsheets, PDFs, images, and other file types into metadata that can be stored, searched, and used to automate business processes. It combines advanced large language models, integrated OCR, chain-of-thought prompting, extraction-specific retrieval-augmented generation, and agentic reasoning techniques to understand document meaning and structure with high accuracy, without requiring custom model training or heavy configuration. Users can choose between Standard and Enhanced Extract Agents, handling everything from basic fields like names, dates, and amounts to complex items such as risky clauses, tables, and graphs, and build Custom Extract Agents with configurable metadata templates that run at scale across folders and repositories.