Unsiloed vs. Cohere Parse

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.

Cohere Parse is a sophisticated vision-language model crafted to adeptly manage and analyze extensive collections of enterprise documents, converting complex multimodal files into structured data that machines can seamlessly understand. Unlike traditional OCR systems, it can interpret tables, forms, diagrams, embedded images, and the overall layout of documents, resulting in clean Markdown that is ready for various downstream applications. This model is specifically designed for business documentation across essential industries such as finance, insurance, and scientific research, and it supports text and images in nine widely spoken global languages. Featuring spatial awareness, it preserves important visual relationships by creating bounding boxes around visual elements, which significantly enhances tasks like retrieval, grounding, and automation. Engineered to handle high-volume production tasks, Cohere Parse guarantees consistent parsing quality and high throughput, even as the volume of documents grows. Its capabilities are applicable in automated document processing, facilitating the extraction of structured information from a diverse array of documents, including but not limited to claims, contracts, and invoices. As such, Cohere Parse emerges as an invaluable tool for organizations aiming to optimize their document management and extraction workflows, ensuring efficiency and precision in their operations. Ultimately, its versatility and effectiveness make it an asset in navigating the complexities of modern documentation.