Image and video decision

Captions

A small team can reproduce a useful subset (auto-captions, simple AI-guided cuts, export) at modest cost; the full product (generative avatars, managed high-volume credits, polished multi-model stack) is harder to match, so consider building a narrow replacement and keep paying for the premium features you need.

Visit website
You pay

$24.99/mo

$300/yr

Read off the official pricing page.

You’d pay instead

$50one-off30 h to build

$200/mo10 h/mo upkeep

On cash alone, building overtakes the subscription at 9 seats.

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 Captions alternatives, with the arithmetic →

What a replacement has to do

  • Upload footage -> auto-transcribe and detect cuts -> apply style-based cuts and captions -> render/export final video

What it still won’t have

  • Generative AI avatars / digital twins
  • In-app AI video generation (creating new footage)
  • Proprietary multi-model editing stacks and high-volume credit tiers
  • Eye-contact correction and some advanced denoise/voice-clone features
  • 100+ built-in edit styles and managed asset library

What remains hard

  • Brand trust20M current users
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 9 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 AI video-editing web app using React (frontend) + Node/Express (backend) + PostgreSQL for metadata and S3 for media. Core features in scope: 1) upload and store video files, 2) transcode and run scene-detection with FFmpeg, 3) generate time-aligned captions via Whisper or AssemblyAI, 4) create an edit plan (simple heuristics + prompt to an LLM) that trims silencers and applies a chosen style, 5) render final MP4 with FFmpeg and provide download. Out of scope: generative video/AI avatars, advanced eye-contact correction, large-scale credit management, mobile apps. Include error handling for failed transcodes and API calls, unit tests for backend endpoints, and an end-to-end test for upload→export flow.
How we checked5 sources · 3/3 runs agreed · evidence score 67

How the score was reached

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

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 quoted from the page