Image and video decision
Facemetrics AI
A competent technical user can reproduce the app's core functionality (on-device face-mesh detection, ratio computations, reports) within a week and modest ongoing maintenance; the vendor shows no apparent durable moats in the supplied pages.
View on the App Store↗$9.99/mo
$120/yr
Read off the official pricing page.
$50one-off28 h to build
$0/mo4 h/mo upkeep
On cash alone, building overtakes the subscription at 1 seat.
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 takes or uploads selfie → app detects facial landmarks → compute ratios/symmetry/feature scores → show report and trend graphs → optionally store scans locally
What it still won’t have
- Polished App Store distribution, reviews, and discoverability
- Built-in in‑app purchase plumbing and Apple subscription management
- Any proprietary tuning, copywriting, UX polish, and continued product iterations from the vendor
What remains hard
- Product polish and ongoing maintenance
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 1 seat.
Money you would actually spend
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
Build an iOS app in Swift (UIKit or SwiftUI) that performs on-device facial analysis using an on-device face-mesh model (MediaPipe/ARKit/ CoreML-exported model). Core features in scope: selfie capture & upload with normalization; 468-point landmark extraction; ratio and symmetry calculations (jawline, eye tilt, facial thirds, golden-ratio comparisons); single-scan detailed report screen and trend graphs comparing multiple local scans; local encrypted storage of scans; export/share PDF report; basic local entitlement gating for paid features. Out of scope: App Store in-app purchase integration (implement a placeholder entitlement), cloud-hosted processing, analytics back-end, and multi-user server. Include error handling for camera/file failures, unit tests for metric computations, and UI tests for capture → report flow.
How we checked
How the score was reached
- Build verdict base78
- 2 cited sources+1
- Price verified on pricing page+3
- Evidence score82
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 · 2
Every page the run actually retrieved.
- official productFacemetrics AI - Face Analysis - App Store
- official pricingFacemetrics AI - App Store pricing section
Integrity checks
What held up, and what did not.
