Documents and notes decision

Reflect

A basic web version (editor + backlinks + embeddings + GPT/Whisper integration) is realistic for a small team to build and self-host, but matching Reflect's full product (mobile apps, polished sync, E2EE and integrations) is more work and not practical to reimplement quickly.

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Subscription$10/month ✓ verified
Initial build80 hours
Monthly upkeep8 hours + $30
Evidence3/3 runs agree

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.

What a replacement has to do

  • Create, backlink, and search personal notes with AI assistance (summarize, rewrite, transcribe).

What it still won’t have

  • Mobile apps (iOS/Android) and native sync polish
  • Production-grade end-to-end encryption implementation and key management
  • Built-in Readwise/Kindle sync and polished web-clipper extensions
  • Product polish, scalability, and ongoing UX/product improvements
  • Managed hosting, backups, and uptime guarantees

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying ischeaper in year one.

On cash alone, building overtakes the subscription at 4 seats.

Paid seatsseats

Money you would actually spend

Keep paying

Subscription price × seats × 12

Build it

AI build APIs + hosting

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

Not run yet
Build a single-tenant web note-taking app using Next.js (React) + Postgres + Prisma + Tailwind; host on Vercel (frontend) and a small managed Postgres (Supabase or Neon). Implement: 1) Markdown editor with backlinks and note metadata, 2) Postgres schema for notes, backlinks, and versions, 3) vector search using OpenAI embeddings stored in a simple vector table (or use pgvector) and a search API to return semantic results, 4) server-side integration with OpenAI GPT-4 for summarization/rewrite endpoints and Whisper for audio transcription, 5) a minimal web-clipper endpoint and a browser extension stub that POSTs clipped content. Out of scope: native iOS/Android apps, full end-to-end encryption key-management, multi-user organizations, and large-scale syncing. Include input validation, error handling, tests for API routes, and CI that runs unit and integration tests.
How we checked6 sources · 3/3 runs agreed · evidence score 67

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 6 cited sources+3
  • Price verified on pricing page+3
  • 3/3 assessment runs agreed+4
  • Evidence score67

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 · 6

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat recorded