Unsiloed vs. ParserBee

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.

ParserBee provides a cloud-based platform designed to extract data from numerous business documents, specifically targeting teams involved in finance, accounts payable, operations, and logistics. Users can opt for pre-existing Parser Templates, craft their own from the ground up, or submit a sample document for the AI-driven template builder to suggest the necessary fields for extraction. This service adeptly retrieves structured data and line items from a broad spectrum of documents, including invoices, purchase orders, receipts, bank statements, and contracts. Furthermore, Data Lab simplifies the process by enabling batch uploads and allowing users to view data in a spreadsheet format, with options to export to Excel, CSV, PDF, or Google Sheets. It also features smooth integration with Google Sheets and Airtable, along with support for workflow automation through tools like Zapier, n8n, Make, and Power Automate, which allows users to easily transfer extracted data to various applications. Developers benefit from access to a REST API, official libraries for Python and Node.js, and an MCP server for greater customization options. The system supports a diverse range of file types, such as PDFs, scans, photographs, spreadsheets, presentations, and email formats, making it a highly adaptable tool for managing data. Users consistently commend the user-friendly interface and powerful features that optimize the data extraction process, significantly boosting productivity across various business sectors. With its comprehensive capabilities, ParserBee stands out as an essential resource for organizations seeking efficient data management solutions.