Health, home and travel decision

Supplements AI

A competent developer can reproduce a useful core (questionnaire, catalog, schedule, reminders, charts) in a few weeks, but the full product value relies on curated content, polished native apps, and an existing user base that are costly to match.

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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-off80 h to build

$50/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 completes a questionnaire -> backend estimates nutrient gaps -> user selects/adds supplements -> system generates a timed supplement schedule and reminders -> user logs adherence and sees progress charts and suggestions.

What it still won’t have

  • Native mobile apps and polished app-store presence
  • Proprietary AI tuning and curated 200+ supplement profiles with editorial content
  • Existing user base, ratings, and aggregated reviews
  • Polish and UX refinements from production usage (repeat edge-case fixes)

What remains hard

  • Brand trust★ Rated 4.8 by our users
  • Execution qualityWell designed supplement tracker
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First-year cost

No published price

Supplements AI 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 PWA supplement tracker using Next.js (React) + Node/Express backend, Postgres for data, Redis for scheduled jobs, and Firebase Cloud Messaging + SendGrid for reminders. Core features in scope: (1) onboarding questionnaire and backend rules engine to estimate 18 nutrient probabilities, (2) seedable supplement catalog (~200 items) with search/filters and interaction metadata, (3) schedule generator that places supplements around meals/sleep/exercise and persists reminder events, (4) push/email reminder delivery and simple 'taken/missed' logging, (5) day-by-day charts and CSV export of logs, (6) basic auth, user settings and privacy controls. Out of scope: training custom ML models, native App Store builds, community reviews, and third-party integrations beyond push/email. Include input validation, retry logic for notifications, background job monitoring, basic unit/integration tests, and deployment scripts (Docker + cloud host).
How we checked1 sources · 3/3 runs agreed · evidence score 56

How the score was reached

  • Partly verdict base52
  • 3/3 assessment runs agreed+4
  • Evidence score56

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 · 1

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! 2 moats quoted from the page