LayoutLM / LayoutAI
The industry-standard multimodal transformer for layout-aware document intelligence and automated information extraction.
Enterprise-Grade Document Intelligence and RAG-Driven Knowledge Synthesis.
DocuWise is a leading AI-powered document intelligence platform designed to transform static unstructured data into interactive knowledge assets. Built on a proprietary Retrieval-Augmented Generation (RAG) architecture, DocuWise enables users to upload massive datasets—including PDFs, technical manuals, and legal contracts—and interact with them via a high-precision conversational interface. Its technical stack leverages advanced vector embeddings and cross-encoder re-ranking to ensure that responses are not only contextually relevant but also cited with granular page-level references. In the 2026 market, DocuWise has positioned itself as a critical bridge for enterprises moving beyond simple chatbots into complex automated workflows. It handles advanced Optical Character Recognition (OCR) for handwritten or low-resolution scans and supports multi-modal inputs, allowing for the analysis of diagrams and complex tables. By providing a secure, SOC2-compliant environment for data processing, it serves as a primary tool for legal, medical, and technical departments that require high-fidelity information extraction without the hallucinations typical of base-model LLMs.
Ability to link information across multiple distinct documents to answer complex comparative queries.
The industry-standard multimodal transformer for layout-aware document intelligence and automated information extraction.
The open-source toolkit for deep learning-based document image analysis and structured data extraction.
Automate contract review and revenue recognition with Generative AI-driven document intelligence.
Deterministic Python-based data extraction from PDF and image invoices using template matching.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Uses specialized computer vision models to map table structures directly into structured JSON objects.
Maintains a long-term vector database of all uploaded content for instantaneous retrieval without re-indexing.
Visual highlights on the original document source for every claim made by the AI.
Autonomous agents that can execute tasks based on document content, such as sending emails or updating CRMs.
Automatic detection and masking of sensitive information during the indexing phase.
Combines BM25 keyword matching with dense vector embeddings for optimal retrieval.
Manually reviewing thousands of contract pages for change-of-control clauses is slow and error-prone.
Registry Updated:2/7/2026
Researchers need to compare outcomes across dozens of clinical trial PDFs.
Support staff struggle to find specific fix procedures in 500-page hardware manuals.