Image and video decision

Clip Recipe

A technically capable developer can build a narrow extractor and personal workflow; reproducing the full polished product (broad platform coverage, export connectors, accuracy tuning, and UI polish) is multi-week and likely better to keep paying for unless you only need a simple workflow.

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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

$100one-off54 h to build

$100/mo6 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

  • User submits a video or post URL → download/ingest media → transcribe audio → parse/transforms transcription to structured recipe (ingredients, steps, equipment, duration) → allow edits/portion-adjustments → save/export/share

What it still won’t have

  • Polished multi-platform UI and user experience
  • Reliability and coverage for many social platforms (edge cases like carousels, pins)
  • Built-in export connectors and polished formatting for third-party apps
  • Ongoing tuning of extraction models for recipe accuracy and different languages
  • Marketing, support, and account/billing management

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

No published price

Clip Recipe 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

—

—

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 Clip Recipe replacement using: Next.js (React) for frontend, Node/Express API, Postgres for storage, AWS S3 for media storage, and OpenAI (or open-source Whisper + LLM) for transcription and NLP. Core features in scope: (1) accept a single video/post URL and fetch/download the media, (2) transcribe audio and produce plain text, (3) run an extraction pipeline that outputs ingredients (with quantities), step-by-step directions, equipment, duration, and portion metadata, (4) UI to view/edit the structured recipe and adjust portion sizes with automatic quantity scaling, (5) export to PDF and provide a Notion export (webhook/API), (6) basic auth and per-user recipe storage. Out of scope: building complex platform-specific scrapers for every social network, OCR from on-screen text, multi-language translation beyond calling a translation API, payment or subscription billing. Include error handling for failed downloads/transcriptions, rate-limit/backoff for provider APIs, and unit tests for extraction logic and portion-scaling.
How we checked3 sources · 3/3 runs agreed · evidence score 59

How the score was reached

  • Partly verdict base52
  • 3 cited sources+3
  • 3/3 assessment runs agreed+4
  • Evidence score59

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.

✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat recorded