Are PatentFig AI and PatentDrawingAI the same kind of tool?

Yes — both are AI generators that turn photos, sketches, and CAD-derived images into patent line drawings. The honest way to choose is to generate the same figure from the same input in both and compare output quality, then weigh the workflow differences: compliance checking, editing, export, and data policy.

Which covers more patent offices?

PatentFig AI checks figures against six offices — USPTO, CNIPA, EPO, JPO, KIPO, and PCT. PatentDrawingAI’s public materials are USPTO-oriented as of 2026; if you file internationally, confirm its coverage with the vendor.

How does editing differ between the two?

PatentFig AI supports chat-to-modify: describe a targeted change and the figure updates without full regeneration, which matters when an attorney marks up a draft. PatentDrawingAI’s described workflow is generation-centric; check its current feature set for editing options.

Which exports vector files?

PatentFig AI exports SVG alongside TIFF, PDF, and PNG, so figures stay editable in vector tooling. PatentDrawingAI’s output is raster-focused per its public materials — verify current formats with the vendor.

What about confidentiality of my invention disclosures?

PatentFig AI states that it does not train models on user data. For any tool handling unfiled disclosures, read the current terms of service yourself — vendor policies can change, and this page reflects public information as of 2026.

How do their prices compare?

PatentFig AI starts free (20 credits); the Basic plan is $50 per month for 500 credits — about 50 figures at roughly $1 each, with yearly billing at about $20/month. PatentDrawingAI’s pricing is published on its own site and changes over time, so compare current pages directly before deciding.

PatentFig AI vs. PatentDrawingAI

Two AI patent drawing generators in the same category. The differences are in what happens after generation: compliance checking, iterative editing, export formats, and data policy.

Try PatentFig AI Run the figure checker

Six-office checking
Chat-to-modify edits
SVG vector export
No training on your data

The 30-second answer

Both tools generate patent drawings from photos, sketches, and CAD-derived images — they are direct competitors in the same category.
PatentFig AI differentiates after generation: compliance checks for six patent offices instead of USPTO only, chat-based targeted edits, consistent multi-view sets, SVG vector export, and no training on user data.
If you file USPTO-only and just need one-shot generation, the fairest test is to generate the same figure in both and compare the output yourself.

Where the two tools overlap

The honest starting point: the core generation job is similar.

AI generation from real inputs

Both accept photos, sketches, and CAD-derived images and produce black-and-white patent line art.

USPTO orientation

Both target 37 CFR §1.84-style output as the baseline.

Speed

Both generate first drafts in minutes rather than the 7–10 days of a drawing service.

Helpful content

PatentDrawingAI maintains a strong article library on costs and examples; PatentFig AI publishes office-by-office guides.

Where PatentFig AI extends the workflow

The differences show up after the first draft is generated.

Six-office compliance checker

Validate figures against USPTO, CNIPA, EPO, JPO, KIPO, and PCT rules before filing, not just USPTO.

Chat-to-modify

Ask for a targeted change — move a numeral, fix a hatch — without regenerating the whole figure.

Multi-view consistency

Design view sets keep proportions and numerals consistent across front/rear/side/top/bottom/perspective.

Vector export and data policy

SVG, TIFF, PDF, and PNG export, with a stated policy of not training on user data.

PatentFig AI vs. PatentDrawingAI at a glance

Based on each product’s public materials as of 2026 — verify current features with the vendors.

PatentDrawingAI

PatentFig AI

Offices covered

USPTO-oriented

USPTO, CNIPA, EPO, JPO, KIPO, PCT

Compliance checker

Not described in public materials

Built-in pre-filing figure checker

Iterative editing

Regenerate-based

Chat-to-modify targeted edits

Vector export

Raster-focused output

SVG plus TIFF, PDF, PNG

Data training policy

Check the vendor’s current terms

Does not train on user data

Pricing model

See its current pricing page

Subscription (free tier; $50/mo · 500 credits · ~50 figures, ~$1 each)

PatentFig AI is the better fit when

You file beyond the USPTO and need CNIPA/EPO/JPO/KIPO/PCT checks
Figures go through review cycles — chat edits beat full regeneration
You need editable vector output (SVG) for downstream tooling
Confidentiality terms require that your disclosures never train models

PatentDrawingAI may serve you just as well when

You file USPTO-only and need one-shot generation without iteration
You mainly want a drawings generator plus its reference articles
You are comparing on price and its current plan happens to fit better

Honest comparison

PatentFig AI vs. PatentDrawingAI FAQ

Run the head-to-head yourself

Generate a figure from your own photo or sketch, run it through the six-office checker, and judge the output.

Try PatentFig AI

Related tools and guides

Patent drawing generator

Generate a patent drawing from a text description.

Figure checker

Validate figures against office rules before filing.

Patent drawing software

The full PatentFig workspace for filing-ready figure sets.

Patent drawing examples

Browse sample patent figures across every category.

Design patent drawing software

Consistent front/rear/side/top/bottom/perspective views.

Vectorize

Convert raster figures to SVG, DXF or vector PDF.

The 30-second answer

Both tools generate patent drawings from photos, sketches, and CAD-derived images — they are direct competitors in the same category.

PatentFig AI differentiates after generation: compliance checks for six patent offices instead of USPTO only, chat-based targeted edits, consistent multi-view sets, SVG vector export, and no training on user data.

If you file USPTO-only and just need one-shot generation, the fairest test is to generate the same figure in both and compare the output yourself.