Audio and podcasting decision

Superwhisper

A small team or single engineer can reproduce the core dictation+transcription+paste workflow in ~30 hours and run it cheaply, but Superwhisper's enterprise compliance (SOC 2), polished cross-platform native UX, managed model catalog, and enterprise features justify keeping the paid product for teams or regulated use.

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Subscription$8.49/month ✓ verified
Initial build30 hours
Monthly upkeep8 hours + $20
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

  • Record microphone or upload audio → run speech-to-text (local or cloud) → apply mode-specific text transformations (prompt/LLM) → paste edited text into the focused app or export transcript.

What it still won’t have

  • Enterprise features (SOC 2, centralized billing, model access control)
  • Polished cross-platform native UX and iOS native app
  • Built-in model catalog and managed unlimited cloud model usage
  • Priority support and volume/enterprise discounts

What remains hard

  • Compliance and regulationSOC 2 Type II certified
  • Brand trusthundreds of thousands rely on Superwhisper to save time.
Read the build prompt

First-year cost

Keep paying

Paying ischeaper in year one.

On cash alone, building overtakes the subscription at 3 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 cross-platform Electron desktop app (Mac & Windows) with a small Python or Node background worker for local ML. In scope: global shortcut to start/stop recording, microphone capture and WAV buffering, local Whisper-based speech-to-text fallback and optional cloud STT via user-provided API keys, a small prompt-driven transformation step (call OpenAI/Anthropic with user-supplied key), clipboard/paste integration to insert results into the active app, file upload processing, settings UI for modes/vocabulary, and basic history. Out of scope: SOC 2, centralized enterprise billing, native iOS client, and large-scale telemetry. Include error handling, basic unit/integration tests, and a README with install and run instructions.
How we checked4 sources · 3/3 runs agreed · evidence score 64

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
  • 3/3 assessment runs agreed+4
  • Hard moats found in the evidence-3
  • Evidence score64

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.

Integrity checks

What held up, and what did not.

✓ Price read off the page✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 2 moats quoted from the page