Design and diagrams decision

PatentFig

A competent developer can build a useful, smaller patent-figure generator for personal or small-firm use within a week and modest monthly cloud/model costs, but reproducing the vendor's proprietary model quality, enterprise guarantees, and compliance assurances is not realistic.

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Subscription$50/month ✓ verified
Initial build40 hours
Monthly upkeep6 hours + $125
Evidence2/3 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. All PatentFig alternatives, with the arithmetic →

What a replacement has to do

  • Upload reference image or enter description → run image-to-line/figure generation model → vectorize/clean output → apply office-export templates and download SVG/TIFF/PDF.

What it still won’t have

  • Proprietary generation quality and ongoing model improvements provided by the vendor
  • Contractual security, DPA/NDA and Trust Center assurances out of the box
  • Enterprise features such as team pipelines, high-volume throughput guarantees and SLA-backed support
  • Polished UX and built-in multi-office compliance testing/certification workflows

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 3 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 self-hosted PatentFig-like web service using Next.js for the frontend, Node/Express for the API, PostgreSQL for metadata, and S3-compatible storage (DigitalOcean Spaces or AWS S3). Use a hosted GPU instance (or managed inference endpoint) to run an image-to-line or image-to-figure model (or call a hosted image-inference API) and implement a raster-to-vector step using an open-source tracer (e.g., potrace via node bindings). Core features in scope: file upload, authenticated user account, one-project workspace, synchronous POST /generate that returns SVG/PNG, versioning (V1, V1.1), simple chat-to-edit flow that accepts textual edits and triggers a regeneration, and export endpoints producing SVG/PDF/TIFF at configurable DPI. Out of scope: training new models, enterprise multi-team billing, legal DPA/NDA contracts, and certified multi-office compliance testing. Include error handling, idempotent request keys, automated tests for upload/generation/export flows, and deployment scripts (Docker + Terraform or DigitalOcean App Platform).
How we checked5 sources · 2/3 runs agreed · evidence score 63

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 5 cited sources+3
  • Price verified on pricing page+3
  • Evidence score63

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 · 5

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