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Shared intelligence for innovation.

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.
OpenRead is a sophisticated AI-powered research platform engineered to solve the bottlenecks of academic literature reviews and scientific data extraction.
Explore all tools that specialize in synthesize scientific literature. This domain focus ensures OpenRead delivers optimized results for this specific requirement.
Explore all tools that specialize in semantic search. This domain focus ensures OpenRead delivers optimized results for this specific requirement.
A low-latency LLM pipeline designed to generate hierarchical summaries categorized by Methodology, Results, and Limitations.
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.
Create an account at openread.academy using academic or professional email.
Connect your ORCID or Zotero profile for existing library synchronization.
Upload research papers in PDF format or paste URLs to OpenAccess articles.
Use the 'Espresso' tool to generate high-level summaries and TL;DRs.
Navigate to the 'Iris' workspace to begin an interactive Q&A session with your library.
Utilize the structural parsing tool to extract tables into editable Markdown formats.
Map the literature landscape using the visual relationship graph feature.
Annotate papers using the integrated smart-note system that links back to source coordinates.
Export synthesized notes and citations in BibTeX for LaTeX compilation.
Set up automated alerts for new papers matching your semantic search queries.
All Set
Ready to go
Verified feedback from other users.
"Highly praised for its PDF parsing capabilities and the Iris workspace, though some users find the credit system for the free tier restrictive."
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