Image and video decision

Vuely, Inc.

A capable engineer can build a focused MVP that produces mockups, estimates, and proposals, but reproducing Vuely's polished rendering performance, tuned imaging models, integrations, and commercial support at scale requires more time and resources than a single developer likely has.

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Subscription$249/month ✓ verified
Initial build80 hours
Monthly upkeep12 hours + $250
Evidence3/3 runs agree

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.

What a replacement has to do

  • Capture site photos + measurements → generate photo-accurate mockup with sign overlay → produce price estimate and one-click proposal (PDF) with signature capture

What it still won’t have

  • Vendor-trained or tuned imaging models and prompt engineering
  • Hosted, optimized rendering pipeline with sub-minute renders
  • Built-in production integrations and export workflows
  • Commercial support, onboarding, and SLA
  • Polished UX and field-tested survey checklists

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying ischeaper in year one.

On cash alone, building overtakes the subscription at 2 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 self-hosted minimal Vuely replacement using Next.js for the frontend, Node.js/Express for the backend, PostgreSQL for metadata, and S3-compatible storage for images. Implement: 1) a mobile-friendly site-survey UI to upload photos + annotate measurements, 2) a measurement/AI-assisted scaling endpoint that applies perspective correction and scale from user input (use OpenCV and an off-the-shelf segmentation model), 3) an image-compositing service that removes backgrounds, rasterizes a sign overlay, and composites it into the photo, 4) a simple rule-driven pricing estimator (materials, size, mounting) persisted in Postgres, and 5) proposal generation that renders a PDF, emails a link, and supports on-screen signature capture. Out of scope: multi-location billing, unlimited concurrent render scaling, and advanced city-code checks. Include error handling, input validation, unit tests for backend logic, and integration tests for the mockup pipeline.
How we checked4 sources · 3/3 runs agreed · evidence score 67

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
  • 3/3 assessment runs agreed+4
  • Evidence score67

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 · 4

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat recorded