AI patent drawing automation: deep learning solution for CAD-to-patent conversion

Client

A patent law firm

Industry

Legal

Services

AI software development, automation

Tech stack

Python, FastAPI, React, PostgreSQL, Google Cloud Platform, U-Net, Docker, Stripe, TensorFlow

Challenge

Converting CADs into compliant patent drawings is a notoriously time-consuming and error-prone process. Patent offices worldwide enforce strict formatting rules, including precise paper margins, line weights, scaling conventions, and view requirements—all of which must be rendered in black-and-white without shading or color. Traditionally, law firms hire specialized illustrators to manually recreate technical drawings from CAD files, a process that could take over 40 hours for complex inventions. Even minor updates to a design meant starting over from scratch. Quality varied from one draftsman to another, and formatting mistakes often triggered costly revision cycles, slowing down the overall patent process and pulling legal teams away from strategic, high-value work. After years of wrestling with inefficiencies, revision delays, and rising costs, the client—an innovative patent company—had reached a breaking point. Exhausted by the limitations of their manual workflow, they began searching for an AI development partner who could help them automate and modernize the process with AI patent drafting. That’s when they turned to ITRex.

Our responsibilities

The client tasked our team with designing and developing an intelligent platform that automates the entire process of converting CAD files into USPTO, EPO, and WIPO-compliant patent drawings.

Solution

Our team built a web-accessible platform with a clean, intuitive React-based front end that allows users to simply drag and drop CAD files for processing. We deployed this solution on scalable cloud infrastructure, enabling it to handle even the most complex CAD models without compromising performance. A U-Net-based deep learning model powers the image-to-image conversion process, re-rendering 3D designs into compliant 2D patent drawings. This model is a convolutional neural network for precise image segmentation that drives many image generation models, including Midjourney and DALL-E. We curated a massive, proprietary dataset of tens of thousands of approved patent drawings from the USPTO, EPO, and WIPO. Our U-Net model was trained on this data to convert intricate 3D geometries into black-and-white technical drawings. The model automatically applies correct line weights, scaling, view types, and all necessary formatting conventions to ensure full compliance. Key features of this AI patent drawing automation platform include:

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Automated drawing generation. The system parses uploaded CAD files and automatically creates compliant patent drawings, including top, side, sectional, and exploded views.

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Built-in regulatory compliance. The AI ensures every drawing adheres to formatting standards, such as required margins, line clarity, sequential numbering, and black ink rendering.

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Instant PDF export. Finished drawings are compiled into print-ready PDFs, properly formatted for immediate submission.

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Seamless revision handling. When a source CAD file is updated, the platform intelligently identifies only the components and views that have changed. By reprocessing only the affected sections instead of the entire drawing set, it reduces revision times from hours to minutes.

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Integrated payment processing. Stripe integration enables secure, hassle-free transactions directly within the platform.

As a result, we delivered a high-performance patent illustration tool that empowers legal teams to generate polished, standards-compliant drawings in a fraction of the time and without relying on external illustrators.