Image and video decision

AI Captions

A single developer can build a minimal pay-per-video captioning service with existing ASR APIs and FFmpeg in about a week; the vendor’s added polish and brand are the main things you’d forgo.

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Built by Sam T, who ships 4 products in this index

You pay

Not priced

No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.

You’d pay instead

$50one-off25 h to build

$30/mo3 h/mo upkeep

No published price to break even against.

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

  • Upload a video, run ASR to get timestamps, render styled burned-in captions onto the video, produce a short watermarked preview, then produce the full unwatermarked video after one-time payment.

What it still won’t have

  • Polished multi-style caption presets and visual preview UI
  • One-click pay-per-video checkout flow tuned to non-technical users
  • Any proprietary optimizations the vendor may use for caption accuracy or rendering performance
  • Customer support and brand trust

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

No published price

AI Captions does not publish a price we could read, so there is nothing to compare against. What building costs is below.

Money you would actually spend

Keep paying
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Subscription price × seats × 12

Build it
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AI build —APIs + hosting —

Time you would spend

—

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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 service (React frontend, Node.js/Express backend, Postgres for jobs/metadata, S3-compatible storage) that: 1) accepts MP4/MOV/WebM uploads with server-side validation and presigned uploads; 2) calls an ASR API (or runs Whisper locally) to produce time-aligned captions; 3) provides a UI to choose caption style (font, color, highlight, border, size, screen spot) and preview settings; 4) produces a short watermarked preview clip (trim + overlay captions + watermark) and a full export pipeline that renders burned-in captions using FFmpeg overlay filters; 5) integrates a one-time payment checkout (Stripe) to unlock full downloads and triggers final rendering; Out of scope: multi-user accounts, team admin features, translation/dubbing, mobile apps. Include error handling, retrying for failed transcode jobs, job queueing (e.g. Bull), logging, and automated tests covering uploads, ASR integration, and export completion.
How we checked3 sources · 2/3 runs agreed · evidence score 81

How the score was reached

  • Build verdict base78
  • 3 cited sources+3
  • Evidence score81

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.

! 2 of 3 runs agreed; the verdict is the majority✓ Citations limited to fetched pages! 1 moat recorded