Unsiloed vs. Sensible

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.

Sensible is an innovative document-processing platform that emphasizes API integration, allowing developers and product teams to swiftly convert unstructured documents into structured data. It effectively pulls information from a variety of formats, including PDFs, images, emails, and spreadsheets, by leveraging both LLM-driven parsing and visual layout-rule engines. Featuring more than 150 pre-designed parsers tailored for common business documents such as bank statements, invoices, and utility bills, organizations can accelerate their deployment timelines while also enjoying the option to develop custom configurations that align with their unique workflows. Furthermore, its classification capability includes a specialized endpoint that automatically identifies the document type before extraction, thereby reducing the necessity for manual sorting of files. Integration is effortless through REST APIs, Webhooks, and SDKs available in JavaScript and Python, which supports document ingestion in both development and production environments, while enabling version control. This all-encompassing approach not only optimizes workflows but also significantly boosts overall document management efficiency, ensuring that businesses can handle their data with ease and precision. As a result, companies can focus on their core tasks without being bogged down by cumbersome document processing challenges.