Design and diagrams decision

Roomy AI

A single capable developer can build a useful web replacement (photo upload → style-driven image generation → save/export) in about a week; the shipped iOS polish, App-Store integrations, and any proprietary model access are what you'd give up.

View on the App Store
You pay

$3.33/mo

$40/yr

Read off the official pricing page.

You’d pay instead

$100one-off32 h to build

$20/mo3 h/mo upkeep

On cash alone, building overtakes the subscription at 9 seats.

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 photo of a room → pick a design style → send photo + style to an image-generation/inpainting API → receive redesigned image(s) → allow simple swaps (furniture, colors) and save/export.

What it still won’t have

  • Polished native iOS App Store distribution and App-Store-specific features (Face ID purchases, localized paywall behaviors)
  • Apple-managed subscription flows and fraud/chargeback handling
  • Any proprietary or vendor-trained models the app may use
  • Polished UX, localization, and performance optimizations of the shipped product

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 9 seats.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
—

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 version of an AI interior-design app using Next.js + React (TS), Tailwind CSS, Node/Express API server, PostgreSQL for saved galleries, and Replicate or Stability API for image-generation/inpainting. Core features in scope: photo upload and preprocessing, style catalog UI (loadable JSON of 100+ styles), API integration to generate styled/inpainted images from a masked room photo, a basic furniture-replacement tool (select region, call inpainting with replacement asset), user gallery with authentication (email sign-in), and export/download. Out of scope: iOS App Store packaging and Apple IAP flow, advanced AR/3D visualization, large-scale multi-tenant billing. Include error handling, retries for external API calls, basic unit/integration tests for the API endpoints, and deployment scripts for Vercel (frontend) and a small managed Postgres DB. Log and limit user image-generation rate to avoid runaway costs.
How we checked1 sources · 2/3 runs agreed · evidence score 81

How the score was reached

  • Build verdict base78
  • Price verified on pricing page+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 · 1

Every page the run actually retrieved.

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