Health, home and travel decision

MacroFactor

A capable developer can reproduce the core food-logging, photo-recognition, and a basic expenditure algorithm in a few weeks, but the full product value depends on proprietary coaching refinements, mobile/watch apps, and workout integrations that are not reproduced here.

Visit website
You pay

$11.99/mo

$144/yr

Read off the official pricing page.

You’d pay instead

$100one-off80 h to build

$50/mo6 h/mo upkeep

On cash alone, building overtakes the subscription at 5 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 MacroFactor alternatives, with the arithmetic →

What a replacement has to do

  • Log foods (typed or photo) → estimate calories/macros → store user weight and log history → compute personalized expenditure and suggested calories → surface daily targets and history.

What it still won’t have

  • Proprietary MF Coach tuning and versioned expenditure algorithm refinements
  • Tight integration and bundle with MacroFactor Workouts (exercise library + demo videos)
  • Mobile apps and Apple Watch experience
  • Community features, published articles, and editorial content

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 5 seats.

Paid seatsseats

Money you would actually spend

Keep paying
—

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 web-based MacroFactor-like app using React frontend + Node.js/Express backend + Postgres. In scope: user signup (email-only), upload or camera photo of a meal, call an external vision API to extract named foods, map items to an embedded nutrition DB (USDA/FNDDS) to compute calories/macros, store daily logs and weight history, implement a simple expenditure algorithm that estimates TDEE from weight trend and logs and returns a daily calorie target, and a dashboard showing today's target and past 30 days. Out of scope: mobile native apps, exercise library/videos, subscription billing, community features. Include validation, error handling for failed API calls, background job for image processing, and unit tests for mapping, algorithm, and API handlers.
How we checked4 sources · 2/3 runs agreed · evidence score 63

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
  • Evidence score63

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