Design and diagrams decision

Magicslides

A single competent developer can build a useful, smaller replacement (LLM calls + PPTX rendering + Google Slides export) in about a week; the vendor's proprietary models, templates, integrations and polish are the main things a DIY will lose.

Visit website
You pay

$29/mo

$348/yr

Per seat. Read off the official pricing page.

You’d pay instead

$100one-off38 h to build

$100/mo6 h/mo upkeep

On cash alone, building overtakes the subscription at 4 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

  • Take user prompt or upload → call LLM/vision models to generate structured slide content → render slides into PPTX/Google Slides format → allow edits and downloads

What it still won’t have

  • Proprietary model access and bundled 'model credits' included in the paid plan
  • The vendor's polished templates, design system presets and ready-made UX polish
  • Built-in mobile apps, Chrome/Figma/ChatGPT integrations shipped by vendor
  • Priority support, managed licensing and account upgrade flows
  • Scale, analytics, and enterprise/whitelabel features

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 4 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 single-developer AI slide generator using Next.js for frontend, Node.js + Express backend, PostgreSQL for minimal metadata, and deployed on Vercel (frontend) + a small VPS or Render (backend). Core features: 1) accept prompts, PDFs, DOCX and YouTube URLs; 2) extract text/transcripts; 3) call an LLM (OpenAI/Anthropic) to produce per-slide title/body/layout JSON and call an image model for slide images; 4) render/output PPTX files and implement Google Slides export via Google Slides API; 5) simple template engine with 6 sample templates; 6) user auth (email or OAuth) and file uploads to an S3-compatible bucket. Out of scope: multi-user billing, mobile apps, advanced design system editor, enterprise SSO. Include error handling for provider failures, input validation, and unit/integration tests for the core transform and export flows.
How we checked3 sources · 2/3 runs agreed · evidence score 84

How the score was reached

  • Build verdict base78
  • 3 cited sources+3
  • Price verified on pricing page+3
  • Evidence score84

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 · 3

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