Unsiloed vs. NaraOps

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.

NaraOps is an innovative web application crafted for operational analytics and reporting, specifically aimed at catering to managers and operational teams. It efficiently processes data from CSV and Excel files, along with historical event records and related datasets to unearth trends, pinpoint root causes, assess potential risks, and discover areas ripe for enhancement. Users can delve into inferred fields and relationships within datasets, adjust mappings, filter results, scrutinize evidence, raise queries, and produce reports suitable for executives, operational teams, one-on-one discussions, and clients alike. Reports can be conveniently exported as PDFs, while evidence and worklists are accessible for download in CSV format. The application directly manages spreadsheet rows in the user's browser, enhancing both security and speed of operation. Moreover, it features an optional document extraction capability, which allows users to send selected files to OpenAI only when they actively choose to do so; any data retrieved in this manner must undergo user review and approval before further analysis can commence. NaraOps excels in facilitating spreadsheet-driven reporting across a myriad of sectors such as retail, services, logistics, support, and manufacturing, establishing itself as an adaptable tool for contemporary operations. This functionality empowers teams to swiftly and effectively make informed decisions based on data insights, ultimately driving organizational success. Furthermore, the user-friendly interface helps streamline workflows, ensuring that operational processes remain efficient.