Scheduling and meetings decision

Amie

A focused self‑hosted workflow (upload→transcribe→summarize→export) is realistic for a single developer in ~30 hours, but duplicating Amie's polished desktop UX, full integrations, and automation features is substantially more work.

Visit website
Subscription$15/month
Initial build30 hours
Monthly upkeep8 hours + $150
Evidence2/3 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

  • Upload or record meeting audio → transcribe audio with an STT API → identify speakers and timestamps → summarize transcript and extract action items with an LLM → save notes and push to calendar/third‑party integrations

What it still won’t have

  • desktop floating/overlay recorder and bot‑free in‑call recording UX
  • deep, prebuilt integrations and polished one‑click exports to many apps
  • built‑in AI scheduling and automatic background recording
  • multi‑language speaker‑labeling quality and proprietary tuning
  • polish around shareable pages and team workflows

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 11 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 self‑hosted minimal AI meeting notes web app using Next.js + Postgres + Supabase auth, deployable to Vercel. In scope: upload or record meeting audio, store audio in S3, call a speech‑to‑text API (e.g., OpenAI/Whisper or AssemblyAI) to generate timestamped transcripts, run an LLM (OpenAI/GPT or Claude) to produce a concise meeting summary and extract action items, map action items to calendar/todo items via Google Calendar and Notion APIs, and provide a web UI to view/edit/share meeting pages and export to Slack/Notion. Out of scope: native macOS/iOS floating overlay recorder, enterprise SSO, advanced multi‑language speaker diarization tuning. Include error handling for failed transcriptions and API rate limits, authentication, and unit/integration tests for transcription→summary→export flows.
How we checked5 sources · 2/3 runs agreed · evidence score 60

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 5 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 · 5

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

! Price not confirmed on the page — this pricing page renders its price in the browser! 2 of 3 runs agreed; the verdict is the majority✓ Citations limited to fetched pages! 1 moat recorded