Documents and notes decision
Heptabase
A competent developer can recreate a useful subset (notes, whiteboard, PDF parsing, LLM chat) in about a week and run it cheaply, but replicating Heptabase's full polished multi-platform product, integrations, and AI Tutor workflow is larger and would likely remain reason to keep the paid product.
Visit website↗$8.99/mo
$108/yr
Read off the official pricing page.
$50one-off30 h to build
$50/mo8 h/mo upkeep
On cash alone, building overtakes the subscription at 7 seats.
Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All Heptabase alternatives, with the arithmetic →
Code Heptabase publishes itself
Not a way out of the subscription - these are the vendor’s own repositories. Worth a look for how they build, and for anything you would have to integrate with.
What a replacement has to do
- Ingest documents and web content, create and link notes/cards on a visual whiteboard, and ask an AI chat to summarize/explain selected sources.
What it still won’t have
- Polished cross-platform native apps and installers (Mac/Windows/Linux/iOS/Android)
- Heptabase-hosted AI Tutor workflows and curated learning sessions
- Built-in premium model access/credit system and vendor-managed scaling
- Integrations advertised (Readwise, Zotero, YouTube transcripts) and their convenience
What remains hard
- Product polish and ongoing maintenance
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 7 seats.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a minimal self-hosted Heptabase-like web app using: React (frontend), Node.js + Express (API), PostgreSQL (data), and an LLM API (OpenAI/Anthropic). In scope: user auth (single-user or basic accounts), upload and OCR/parse PDFs into text, create and position note cards on a zoomable whiteboard canvas, store bi-directional links between notes, a web-clipper endpoint to save page text+URL, and an AI chat endpoint that sends selected document snippets to an LLM and returns summaries. Out of scope: native desktop/mobile installers, multi-tenant billing, sophisticated AI Tutor sequencing, and third-party sync integrations. Include error handling for uploads and API failures, basic tests for parsing, DB migrations, and Docker-based deployment instructions.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 4 cited sources+3
- Price verified on pricing page+3
- Evidence score63
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Cited sources · 4
Every page the run actually retrieved.
- official productHeptabase — Home
- official pricingHeptabase Pricing
- open sourcesiyuan-note/siyuan
- open sourcecodexu/note-gen
Integrity checks
What held up, and what did not.
