Compare Sunflower Lab IDP vs. Unsiloed

The IDP solution efficiently extracts critical information from enterprise documents with an impressive accuracy rate of up to 99%, allowing organizations to reduce their document-processing time by at least 50%. It provides ready-to-use solutions for common document types such as IDs, receipts, and invoices, along with tailor-made options that are trained on your specific data to manage unique forms and documents pertinent to your operations, all while evolving with changing document formats. Its document-analysis features enable the extraction of text, tables, key-value pairs, selection marks, and overall document structure, while also comprehending layout to discern section relationships. The integration capabilities are versatile, seamlessly connecting with your existing ERP systems and workflow tools. As a cloud-based offering, this solution eliminates hardware constraints and the hassle of server maintenance, and you won’t incur additional costs for OCR, AI models, or RPA services. Furthermore, the model is highly customizable, allowing you to pay solely for the features and volume that suit your needs, making it a cost-effective approach for modern businesses. This level of adaptability ensures that the solution can scale alongside your company as it grows and evolves.

Unsiloed AI is an enterprise document intelligence platform built to transform unstructured documents into structured, LLM-ready data. The platform processes PDFs, images, spreadsheets, scans, and multimodal files, then outputs clean JSON, Markdown, or structured fields for AI agents, LLM applications, vector databases, and data warehouses. Its core capabilities include parsing, extraction, and document splitting, allowing teams to use each function independently or chain them into a full production pipeline. Unsiloed’s parser converts complex documents into Markdown while preserving structure across text, tables, charts, figures, forms, handwriting, signatures, and visual hierarchy. Its extraction engine pulls schema-specific fields into JSON and uses domain awareness to understand documents such as invoices, contracts, financial reports, healthcare records, and regulatory filings. Its splitting tools can separate mixed files into individual documents or break long documents into retrievable chunks while preserving parent-child relationships and surrounding context. The platform is powered by proprietary dual-stream vision models that combine a data stream for tokens and entities with a layout stream for bounding boxes, alignment, indentation, and visual structure. Unsiloed is designed to solve the problem of fragile OCR and DIY pipelines that break when document layouts change. For enterprise AI teams, Unsiloed provides a more reliable document layer for turning high-value unstructured data into assets that can be searched, reasoned over, and used in production AI systems.