Chaptora
Browser-based book editor for fiction and non-fiction authors: AI grounded in your chapters, Canon and research, with every edit shown as a red/green diff you accept or reject.
A startup from Austria.
Browser-based book editor for fiction and non-fiction authors: AI grounded in your chapters, Canon and research, with every edit shown as a red/green diff you accept or reject.
A startup from Austria.
This page is designed to help you find out whether Chaptora is good and if it is the right choice for you.
Chaptora is a book editor in the browser with AI that is grounded in your own material. Before it suggests anything, it reads the current chapter, auto-generated synopses of earlier chapters, your project's writing style and a voice sample of your own prose, and matching passages from the research you upload (PDFs, Word and Excel files, web pages, YouTube transcripts and more). A Canon of confirmed characters, places, objects and events keeps the AI consistent with your story; scans flag contradictions, and nothing enters the Canon without your confirmation. Every AI edit arrives as a red/green diff you accept or reject, one edit or one chapter at a time. There is no button that generates a novel.
The editor covers the whole workflow: chapter structure with front and back matter, Word import, version history, citations as chapter endnotes with a Chicago-style bibliography, and export to print-ready PDF in seven Amazon KDP trim sizes on every plan, plus reflowable EPUB 3 and Word (DOCX) with the book layout on paid plans.
Manuscripts and research are never used to train AI models. The interface is English; manuscripts can be written in any language, including German, French, Spanish, Italian, Dutch, and Portuguese.
Octavo is free and includes PDF export with a Chaptora cover page. Quarto costs $20 per month or $200 per year and adds EPUB, Word (DOCX) and PDF export without the cover page. Folio costs $100 per month or $1,000 per year. Prices are in USD.
Official pricing: https://chaptora.com/pricing ยท Export documentation: https://chaptora.com/docs/export
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Reviewable AI edits
Every AI edit arrives as a red/green diff you accept or reject, one edit or one chapter at a time.
AI grounded in your research
Upload PDFs, Word and Excel files, web pages and YouTube transcripts; answers show which sources were used, with Chicago-style citations.
Canon for story continuity
Confirmed characters, places, objects and events keep the AI consistent; scans flag contradictions. Nothing enters the Canon without your confirmation.
KDP-ready export
Print-ready PDF in seven Amazon KDP trim sizes on every plan; EPUB 3 and Word (DOCX) with the book layout on paid plans.
No training on your manuscript
Manuscripts and research are never used to train AI models.
Chaptora grew out of a simple observation: authors were stuck copy-pasting between an AI chat window and their manuscript, with an AI that knew nothing about their book and quietly rewrote their words. Chaptora brings that same workflow to book writing: the AI lives inside the project, reads the author's own sources, and proposes changes the author reviews and approves. Never silent rewrites.
Generic AI chat tools rewrite text invisibly and know nothing about your book, while research tools like NotebookLM understand your sources but don't write alongside you. Chaptora combines both: a full book-writing environment (Chapter Tree with front/back matter, Chicago-style citations with auto-generated bibliography, PDF and EPUB export) with AI that is grounded in your own research and always keeps you in control through diff-based approval. You go from research to a publish-ready file in one tool.
Three groups: non-fiction authors and researchers organising hundreds of pages of factual material who need accurate, grounded writing with proper citations; fiction authors who want help with world-building, chapter structuring, and getting unblocked; and academics or students looking for a NotebookLM-style research companion that actively writes with them instead of only summarising.
Chaptora is a context-aware AI text editor for books and long-form documents: an AI that knows your whole project and writes alongside you. Three things set it apart: (1) No silent overwrites: every AI change is shown as a red/green diff the author must explicitly accept or reject. (2) A project brain: the AI is grounded in the author's own uploaded Sources (PDFs, URLs, YouTube transcripts, files) via vector search instead of free-form hallucination. (3) The Add Context picker: authors attach a specific Source or prior Chapter directly to a prompt, so they can point the AI at exact material without prompt engineering.
A TypeScript monorepo: the frontend is TanStack Start (SSR React) with Tailwind, shadcn/ui, TanStack Query, and a Tiptap v3 rich-text editor; the backend is NestJS with Drizzle ORM; data lives in Neon Serverless Postgres (EU, Frankfurt) with pgvector for embeddings; files in Cloudflare R2; auth via Clerk. AI runs on large language models from major providers through a model picker, and manuscripts are never used for training. PDF export via Puppeteer, plus EPUB 3 and Word (DOCX) generation.
We have collected here some useful links to help you find out if Chaptora is good.
Check the traffic stats of Chaptora on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of Chaptora on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of Chaptora's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of Chaptora on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
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