Leximancer
Transform unstructured text into objective visual intelligence with Bayesian concept mapping.
Accelerate research with AI-powered literature synthesis and intelligent paper parsing.
OpenRead is a sophisticated AI-powered research platform engineered to solve the bottlenecks of academic literature reviews and scientific data extraction. At its core, OpenRead utilizes a proprietary high-fidelity PDF-to-Markdown parsing engine, which uniquely preserves the structural integrity of complex scientific documents including LaTeX formulas, multi-column tables, and hierarchical citations. By 2026, the platform has evolved into a comprehensive Research OS, featuring 'Iris', a contextual AI workspace that allows users to interrogate entire libraries of documents simultaneously. The platform's market position is defined by its ability to bridge the gap between traditional reference managers like Zotero and modern LLM capabilities. It serves PhD students, R&D departments, and medical researchers by automating the extraction of methodologies, results, and critical insights from millions of indexed papers via its semantic search layer. OpenRead's technical architecture is optimized for low-latency retrieval-augmented generation (RAG), ensuring that AI-generated summaries are grounded in specific, verifiable citations from the uploaded or indexed literature.
A low-latency LLM pipeline designed to generate hierarchical summaries categorized by Methodology, Results, and Limitations.
Transform unstructured text into objective visual intelligence with Bayesian concept mapping.
The AI-driven research engine for scientific literature synthesis and lab protocol automation.
The open-source study builder for high-precision behavioral research and online experiments.
Open-source active learning for accelerating systematic literature reviews and evidence synthesis.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
A RAG-based interface that allows cross-document interrogation across hundreds of PDFs simultaneously.
Proprietary OCR and layout analysis engine that converts complex scientific PDF layouts into clean Markdown.
Visualizes citation networks and conceptual relationships using a force-directed graph algorithm.
Semantic search index spanning over 300 million academic papers with natural language querying.
Bi-directional linking between notes in the Iris workspace and the exact coordinate (page/paragraph) in the PDF.
One-click generation of citation metadata following standard schemas.
Manually reading hundreds of papers to identify gaps in existing research.
Registry Updated:2/7/2026
Export synthesized table of findings.
Ensuring a technical invention has not been previously published in obscure scientific journals.
Quickly extracting clinical trial results across multiple papers for a meta-analysis.