Unsiloed vs. Parsebridge

Unsiloed AI is a document layer for enterprise AI that converts complex unstructured files into clean JSON, Markdown, and structured data. The platform is built for organizations whose most valuable information lives inside PDFs, scanned documents, images, spreadsheets, contracts, invoices, reports, filings, forms, and other hard-to-parse formats. Unsiloed helps AI teams avoid building brittle OCR, parser, and post-processing pipelines by providing a production-ready API for document parsing, field extraction, and document splitting. Its parsing capability converts PDFs, scans, and images into LLM-ready Markdown while preserving tables, figures, text hierarchy, page structure, signatures, handwriting, and visual context. Its extraction capability pulls specific fields into JSON using schemas, confidence thresholds, and domain-aware logic that can understand context such as line items, payment terms, clauses, totals, and references. Its splitting capability separates multi-document files into individual documents and breaks long files into retrievable chunks for RAG, agent workflows, and search systems. Unsiloed uses proprietary dual-stream vision models that process content and layout in parallel, then fuse them through cross-attention so the system can reason over what a document says and how it is structured. The platform’s architecture includes attention-guided heatmaps, typed document regions, layout-aware processing, and domain-specific decoding for industries such as finance, legal, healthcare, and enterprise operations. It is designed to handle edge cases that traditional OCR often misses, including nested tables, merged cells, multi-page tables, figures, handwritten notes, forms, and documents with mixed formats. Teams can connect data sources such as S3, SharePoint, Drive, Snowflake, or a document management system, then send structured outputs into LLMs, AI agents, vector databases, or analytics warehouses.

Parsebridge is a cutting-edge API that specializes in parsing PDF documents, transforming them into neatly organized Markdown format. This powerful tool effectively extracts various elements such as text, tables, and other data from PDF files, specifically aimed at developers seeking robust document parsing capabilities on a large scale. It is capable of handling complex PDF structures, including intricate tables, multi-column designs, nested formats, and even scanned pages, all through a single API request, simplifying the conversion of challenging components that often perplex other parsing solutions. Users can anticipate outputs that are clear and accurate, as Parsebridge proficiently parses merged cells, nested headers, and complex layouts, avoiding the disarray typical of less sophisticated parsers. Furthermore, it provides a user-friendly live testing feature, enabling users to either input a PDF URL or upload a document directly to the preview page for immediate Markdown generation, without requiring any account setup. At present, the API is focused exclusively on PDF file support, ensuring top-notch extraction quality for documents that are up to 100MB in size. By leveraging Docling, an acclaimed open-source parser recognized for its exceptional table extraction and layout management, Parsebridge streamlines the necessary infrastructure, OCR capabilities, scaling, and API functionalities, delivering a hassle-free experience for its users. Overall, this comprehensive approach positions Parsebridge as an indispensable resource for those in need of effective and reliable PDF parsing solutions, making document handling simpler and more efficient.