Documents and notes decision
v2md
A competent developer can reproduce the core local voice→Markdown workflow in about a week, but the full product's polished mobile integrations, watch/action-button support, and app-store UX are non-trivial and would be lost by a minimal replacement.
Visit website↗Built by Simon Liang, who ships 3 products in this index
Not priced
No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.
$50one-off19 h to build
$30/mo3 h/mo upkeep
No published price to break even against.
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 v2md alternatives, with the arithmetic →
What a replacement has to do
- Record a voice memo, transcribe audio to text with an ASR/LLM API, post-process into structured Markdown with an auto-generated title and flow tags, save/export the .md file locally (Obsidian-compatible).
What it still won’t have
- Polished mobile UX and deep platform integrations (Apple Watch, Action Button)
- Bundled offline/on-device transcription
- Unlimited transcription quotas and vendor-managed scaling
- Polish around shortcuts, accessibility, and app-store distribution
What remains hard
- Product polish and ongoing maintenance
First-year cost
No published price
v2md does not publish a price we could read, so there is nothing to compare against. What building costs is below.
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 simple local-first Voice→Markdown desktop app using Electron + React for UI and Node for background jobs. Core features in scope: (1) record audio (wav/m4a) from microphone and save locally; (2) upload audio to a configurable speech-to-text API (configurable API key) and retrieve transcript; (3) post-process transcript into a Markdown file with a generated 1-line title and AI-generated flow tags; (4) list, play, delete recordings and export .md files to a chosen folder (Obsidian-compatible frontmatter optional); (5) basic search over saved notes. Out of scope: Apple Watch/action-button shortcuts, app-store packaging, multi-device sync, and offline on-device ASR. Include robust error handling for failed uploads/transcriptions, retry/backoff, and file I/O errors. Provide unit tests for transcription and Markdown conversion logic, and end-to-end integration tests for the recording→transcription→export flow.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 4 cited sources+3
- Evidence score60
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 productv2md — official product page
- official docsv2md Features
- open sourcecjpais/Handy
- open sourceZackriya-Solutions/meetily
Integrity checks
What held up, and what did not.
