Kahubi vs NotebookLM
NotebookLM does one thing remarkably well, for free: upload sources and get grounded answers with citations back. Kahubi is built for what comes around that — managing a real library, running methods, and shipping a manuscript. Here is an honest comparison for research work.
What NotebookLM does well
Credit where it's due — these are real strengths, and for some workflows they are exactly what you need.
- Fast, grounded Q&A over the sources you upload, with citations back to them
- Audio overviews that turn source material into a listenable summary
- Free to use, with the polish you would expect from Google
Where Kahubi differs
A research library, not a notebook of uploads
Kahubi manages an actual reference library: import via BibTeX, RIS, PDFs, or Zotero sync, search and filter by author, year, and tags, attach PDFs, and export citations in any major format. The agent works across all of it — and can search OpenAlex and the web to import papers you don’t have yet.
From answers to output
Grounded answers are the starting point in Kahubi, not the product. The same agent writes into a real LaTeX manuscript (compiled to PDF, exported to .docx/.tex), runs your statistics, screens papers for a systematic review, and analyzes interview transcripts — each step landing in your project, in your citation style, in your voice.
Interviews are data here, not just sources
Kahubi transcribes your interview recordings with speaker labels in 99+ languages on an EU endpoint — a hard requirement under many ethics approvals — then runs thematic, narrative, or grounded-theory analysis across all transcripts and writes the findings into a draft.
A privacy posture made for research data
Kahubi is operated by a Swedish company under the GDPR: no training on your content, EU processing for transcription, documented subprocessors, and deletion on request. Unpublished manuscripts and participant data are treated as the sensitive material they are.
Feature comparison
| Capability | NotebookLM | Kahubi |
|---|---|---|
| Chats with your full library | Partialgrounded Q&A within a notebook’s uploaded sources | Yesthe agent reads, searches, and cites your whole library |
| Edits a real LaTeX manuscript (compiled to PDF) | — | YesLaTeX → PDF compile built in, plus .docx and .tex export |
| Systematic review flow with PRISMA support | — | Yesdefine → search → screen → written review (PRISMA, MOOSE, Cochrane) |
| Statistics on your CSVs (t-tests, ANOVA, regression…) | — | Yesfrom t-tests to PCA and Cronbach’s alpha, results land in your draft |
| Interview transcription processed in the EU | Partialaudio files can be added as sources | Yesspeaker labels, 99+ languages, AssemblyAI EU endpoint |
| Learns your writing voice from your papers | — | Yesa style profile learned from your own publications |
Last reviewed August 2026. Based on each product's public materials — features change, so verify details on their site. Spotted something out of date? Tell us and we'll fix it.
Choose NotebookLM if…
You need free, grounded Q&A and summaries over a bounded set of documents, and the output you need is understanding.
Choose Kahubi if…
You need a workspace where the understanding becomes a screened review, an analysis, or a compiled manuscript — with EU-grade handling of research data.
Kahubi pricing
Simple monthly plans, cancel anytime. A real free tier to start with, and predictable monthly cost on every paid plan.
Try Kahubi on a small project
For a single ongoing study
For active researchers
For labs and heavy users
Kahubi vs NotebookLM — common questions
NotebookLM is free — why would I pay for Kahubi?
Can Kahubi answer questions across my sources like NotebookLM?
How do the two handle audio?
What about data protection for participant data?
Try the Kahubi side of the comparison
Sign up free, import your library in minutes, and run one real task — a screening round, an analysis, a draft — before you decide.