Unsiloed vs. QDox

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.

QDox simplifies the process of extracting and managing data from various unstructured documents such as invoices, contracts, and receipts. By utilizing cutting-edge artificial intelligence and machine learning methodologies, the platform guarantees outstanding accuracy and efficiency in document processing tasks. Companies that implement QDox can create customized workflows to gather essential information from multiple document formats, allowing for effective data application as required. With its pre-trained models capable of handling over 100 different document types across numerous industries, QDox showcases significant flexibility. Furthermore, the inclusion of a Developer Tool Suite, along with a human-in-the-loop framework and pre-built components, reduces development time by an impressive 70% without sacrificing precision. This forward-thinking strategy not only boosts organizational productivity but also enables teams to concentrate on their primary business goals. As a result, QDox proves to be an invaluable asset for companies looking to optimize their data management processes.