The problem
Research generates knowledge that lives in your head. Paper summaries. Half-formed hypotheses. Connections between sources. When you ask an AI to help you think through a problem, it doesn't know any of that. You re-explain your entire research context before you can get useful help.
How researchers use Hjarni
Keep your literature notes, research questions, and synthesis documents in Hjarni. Organize by project or theme. Connect Hjarni to ChatGPT or Claude and your AI has access to everything you've written. It finds patterns. Spots gaps. Drafts arguments that build on your actual reading.
A typical researcher setup
- Literature notes folder — one note per paper with key findings and your commentary
- Research questions folder — open questions, hypotheses, things to investigate
- Synthesis folder — draft arguments, thematic summaries, literature reviews
- Methods folder — data collection protocols, analysis approaches, tool notes
- AI instructions — "Always cite which of my notes you're drawing from"
A concrete workflow
You've read 30 papers on knowledge transfer in distributed teams. Each one has a note in Hjarni with your summary and key takeaways. You ask Claude: "What are the main tensions in the literature on knowledge transfer barriers?" Claude reads your notes and synthesizes across them. It cites your annotated papers. Not generic training data.
New paper? Add a note. Next conversation already includes it.
Why not just use Zotero or a reference manager?
Reference managers handle citations and PDFs. But your thinking — the annotations, the connections, the questions — lives somewhere less structured. Hjarni gives that thinking a home your AI can actually read.
An AI that knows what you've read can help you think. One that doesn't is just a search engine.
What you get
- Your AI reads your research — literature notes, synthesis docs, all of it
- Folder-level AI instructions — different conventions for different research projects
- Wiki-links — connect notes to build a web of ideas
- Full-text search — find anything across your entire knowledge base
- Collaboration — share a research folder with your lab or collaborators
- Markdown export — your notes are yours, always