What is NNScholar?

NNScholar is a desktop AI research workspace for academic and scientific work. It combines multi-source literature search, PDF reading and chat, evidence tracking, citation verification, and AI research agents in one place. Researchers use it to move from a research question to a traceable manuscript, keeping sources, notes, and drafts connected.

How to use NNScholar?

1. Start with a research question or material in Chat and review the proposed plan. 2. Search literature via PubMed, Google Scholar, Wanfang, Semantic Scholar, or arXiv, then save useful papers to Library. 3. Read sources in the PDF reader, chat with the paper, translate, annotate, and take notes. 4. Build an evidence board connecting claims, sources, and decisions. 5. Draft, revise, and export the manuscript, then prepare submission materials. Start in the web workspace, then move long-running projects to NNScholar Desktop.

Core features of NNScholar

Literature Search: AI literature review from a topic, DOI, PMID, arXiv, or research question
PDF Reading: chat with PDF, translate, annotate, and ask questions in paper context
Research Space: paper library with notes, files, conversations, stages, and outputs
Writing & Submission: AI academic writing workflows for outlines, drafts, figures, and submission materials
AI Research Agents: organize evidence, check sources, and draft next steps
Evidence Board: connect claims, sources, decisions, risks, and follow-up actions
Citation Tracing: follow references, related papers, and topic updates from seed literature
Academic Skills: reusable data extraction workflows for review, synthesis, verification, and writing