Forms and surveys decision

Magicform

A capable technical user can realistically build and run a minimal replacement in about a week using existing LLM APIs and libraries; the vendor's main durable advantage is brand recognition rather than unreplicable data or infrastructure.

Visit website
You pay

$7.42/mo

$89/yr

Read off the official pricing page.

You’d pay instead

$100one-off34 h to build

$25/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 Magicform alternatives, with the arithmetic →

What a replacement has to do

  • User provides content (text/URL/YouTube/PDF/image) → extract text/transcript → call LLM to generate question set → present editable quiz UI → export/save (Google Forms, PDF, link).

What it still won’t have

  • Refined proprietary prompts and iterative model tuning used by the hosted product
  • Polish of a production UI, undo/UX edge-cases, and polished export templates
  • Hosted reliability, scaling, and account/billing workflow
  • Any proprietary integrations or enterprise support SLAs

What remains hard

  • Brand trustTrusted by top universities and companies
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
—

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 AI quiz generator web app using Next.js (frontend), Node.js + Express (API), Postgres (storage), OpenAI API (LLM), youtube-transcript-api, pdf-parse (PDF text), and Tesseract/ocr for images; implement Google OAuth sign-in, endpoints to upload/paste content, extract text/transcripts, call the LLM with prompt templates to produce structured MCQs, persist quizzes, provide an editor UI to adjust questions, and add export to Google Forms and PDF. Out of scope: multi-tenant billing, enterprise SSO, mobile apps, and advanced analytics. Include error handling, retries for external APIs, basic unit/integration tests, and a README with deployment steps (Heroku/Render or Vercel + managed Postgres).
How we checked4 sources · 2/3 runs agreed · evidence score 89

How the score was reached

  • Build verdict base78
  • An open-source build was found+5
  • 4 cited sources+3
  • Price verified on pricing page+3
  • Evidence score89

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