Unsiloed
Unsiloed AI is a document processing platform that turns PDFs, images, spreadsheets, scans, and other unstructured files into JSON and Markdown that LLMs and AI agents can use. The platform acts as a document layer for enterprise AI, helping teams parse, extract, and split complex documents without relying on brittle OCR pipelines. Its proprietary dual-stream vision models read both content and layout, preserving tables, figures, forms, signatures, handwriting, hierarchy, and document structure. Unsiloed can extract structured fields into JSON, convert documents into LLM-ready Markdown, and split multi-document files or long documents into retrievable chunks. The platform supports workflows across financial reports, legal contracts, invoices, healthcare records, regulatory filings, scanned documents, spreadsheets, and mixed-layout enterprise files.
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Restructured
Restructured is an AI-powered platform designed to help businesses extract insights from unstructured data at scale. Whether dealing with documents, images, audio, or video, it combines LLM capabilities with advanced search and retrieval methods to not only index information but also understand it in context. Restructured transforms massive datasets into actionable insights, making complex data easy to navigate and analyze.
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Upstage Document Parse
Upstage Document Parse transforms complex documents, PDFs, scanned images, spreadsheets, and slides containing text, tables, charts, and even handwriting, into structured, machine‑readable HTML or Markdown with enterprise‑grade speed and accuracy. Leveraging advanced layout understanding, it recognizes complex tables, charts, and element coordinates, processes pages at an average of 0.6 seconds each (100 pages in under a minute, 5–10× faster than competitors), and delivers over 5% higher layout and table recognition accuracy (TEDS: 93.48, TEDS‑S: 94.16). Easily invoked via a REST API or deployed on‑premises or through marketplaces like AWS, it fits seamlessly into existing pipelines using simple client libraries. Use cases span retrieval‑augmented enterprise search, AI‑powered document summarization, legal and compliance digitization, and financial report processing, preserving intricate layouts and ensuring clean, searchable outputs for downstream LLM workflows.
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Docling
Docling is an easy-to-use, self-contained, MIT-licensed open source toolkit for converting messy documents into structured data and simplifying downstream document and AI processing. It can parse many popular document formats into a unified and richly structured Docling Document, including PDF, DOCX, PPTX, XLSX, HTML, Markdown, AsciiDoc, CSV, images, audio, and scanned pages through an OCR engine of the user’s choice. Docling detects tables, formulas, reading order, chunks, bounding boxes, page headers and footers, pictures, captions, code, list items, paragraphs, cells, and document structure, making extracted content easier to process, search, and ingest into AI, RAG, and agentic systems. It can export parsed documents to JSON, text, Markdown, HTML, and Doctags, giving developers flexible outputs for pipelines and applications. Docling stores and traverses components according to reading order, partitions documents into bite-sized contiguous text chunks.
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