Audio and podcasting decision

Alitu

A capable developer can build a working upload→clean→transcribe→edit→publish workflow in ~30 hours and run it cheaply, but Alitu's built-in browser recorder, double-ender video, music library and polished one-click hosting integrations are non-trivial to replicate fully — so building a useful subset is realistic, replacing the complete product is not.

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Subscription$38/month ✓ verified
Initial build30 hours
Monthly upkeep8 hours + $80
Evidence3/3 runs agree

No open-source build does this yet

Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.

What a replacement has to do

  • User records or uploads audio → automatic audio cleanup & leveling → generate transcript → edit via transcript/waveform → export episode and publish to RSS/host

What it still won’t have

  • Built-in multi-participant browser recorder / double-ender video recording
  • Branded hosted recording studio link and built-in chat
  • Royalty-free music library and integrated transitions
  • One-click publishing integrations to platforms (Alitu-managed hosting workflow)
  • Some automated advanced 'magic filters' and polishing tuned by vendor

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 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 minimal self-hosted podcast production app using: React for frontend, Node.js (Express) backend, PostgreSQL for metadata, S3-compatible storage for audio, and a task queue (BullMQ). Implement: 1) upload endpoint and UI for importing audio files; 2) background audio processing pipeline using open-source tools (ffmpeg + RNNoise or SoX) to perform noise reduction, leveling, hum removal and trimming; 3) transcription step calling an external ASR API (or local Whisper) and storing word-level timestamps; 4) transcript-based editor UI that maps transcript to waveform and supports cut/undo/export; 5) MP3 export with ID3 tags and an auto-generated RSS feed + simple static podcast website. Out of scope: live multi-party browser recorder, double-ender video sync, royalty-free music library, paid-scale analytics. Include error handling, logging, retries for async jobs, CI tests for upload→process→transcribe→export flow, and basic unit/integration tests for APIs.
How we checked3 sources · 3/3 runs agreed · evidence score 62

How the score was reached

  • Partly verdict base52
  • 3 cited sources+3
  • Price verified on pricing page+3
  • 3/3 assessment runs agreed+4
  • Evidence score62

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 · 3

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