There is a bevy of AI-to-CAD tools coming out. Some are finding users; some are raising millions in funding. Many new ones are coming out all the time, so we waded through all of the options we could find to give you an overview. What do these tools mean for us? And what is out there?
Generally, the tools fall into four categories:
AI Plug-ins and Co-pilots: These tools plug into existing CAD tools or live in them. They tie Claude to Fusion or add an AI functionality to a CAD program. These tools live inside or alongside existing software and act as a handy AI assistant for you while using that particular tool.
Workflow and automation tools: These AI tools automate an entire workflow from start to finish, so they can take your scan and turn it into a mold file. These tools can also automate a particular process or conversion, for example, taking 2D drawings into 3D models for BIM.
Checkers: These tools don’t author; they check your CAD file, your assembly for errors, and whether you’re compliant.
Text to STL: Also called text to CAD, these tools use existing LLMs to take a prompt and turn it into a CAD or STL file.
Checkers
The two I’d like to focus on for now are checkers and Text To STL. Checkers are now quite overlooked. But if we look at what LLMs are very good at—categorizing and matching things—they could become very powerful. AI, more generally, is great at spotting patterns and deviations from them. You can review their work, and they just highlight mistakes. This means they can make mistakes, but you can ignore them. And it means they take dreary work out of your hands and help you be more successful and faster, without threatening your work. There’s also a lower chance of developing faulty geometry; more importantly, faulty geometry that you won’t know is faulty until it’s too late. Checkers, therefore, could very well achieve broad adoption much more quickly than other tools, where people may be fearful of being replaced or of creating faulty CAD files. Checkers are your allies, while the other tools could be a threat. This is why we should pay close attention to these.
Text-to-STL
Text-to-STL tools are very crude and easy to dismiss. Engineers, in particular, can easily overlook the impact of these tools because they replace them, their craft, and their tools. But these tools can democratize the creation of files far more than the others. They could take millions of people to create what they need. This could make 3D printing, though desktop machines and services, much more meaningful and accessible to millions. This could be the Cambrian explosion moment that we’ve been waiting for in additive manufacturing. Yes, these tools suck at making good geometry. And yes, they suck at technical parts. Maybe they’ll get better, but let’s imagine that they only kind of get a little better. They’re still easy, but you couldn’t make a spoiler for your car with them. But, ima
There is a bevy of AI-to-CAD tools coming out. Some are finding users; some are raising millions in funding. Many new ones are coming out all the time, so we waded through all of the options we could find to give you an overview. What do these tools mean for us? And what is out there?
Generally, the tools fall into four categories:
AI Plug-ins and Co-pilots: These tools plug into existing CAD tools or live in them. They tie Claude to Fusion or add an AI functionality to a CAD program. These tools live inside or alongside existing software and act as a handy AI assistant for you while using that particular tool.
Workflow and automation tools: These AI tools automate an entire workflow from start to finish, so they can take your scan and turn it into a mold file. These tools can also automate a particular process or conversion, for example, taking 2D drawings into 3D models for BIM.
Checkers: These tools don’t author; they check your CAD file, your assembly for errors, and whether you’re compliant.
Text to STL: Also called text to CAD, these tools use existing LLMs to take a prompt and turn it into a CAD or STL file.
Checkers
The two I’d like to focus on for now are checkers and Text To STL. Checkers are now quite overlooked. But if we look at what LLMs are very good at—categorizing and matching things—they could become very powerful. AI, more generally, is great at spotting patterns and deviations from them. You can review their work, and they just highlight mistakes. This means they can make mistakes, but you can ignore them. And it means they take dreary work out of your hands and help you be more successful and faster, without threatening your work. There’s also a lower chance of developing faulty geometry; more importantly, faulty geometry that you won’t know is faulty until it’s too late. Checkers, therefore, could very well achieve broad adoption much more quickly than other tools, where people may be fearful of being replaced or of creating faulty CAD files. Checkers are your allies, while the other tools could be a threat. This is why we should pay close attention to these.
Text-to-STL
Text-to-STL tools are very crude and easy to dismiss. Engineers, in particular, can easily overlook the impact of these tools because they replace them, their craft, and their tools. But these tools can democratize the creation of files far more than the others. They could take millions of people to create what they need. This could make 3D printing, though desktop machines and services, much more meaningful and accessible to millions. This could be the Cambrian explosion moment that we’ve been waiting for in additive manufacturing. Yes, these tools suck at making good geometry. And yes, they suck at technical parts. Maybe they’ll get better, but let’s imagine that they only kind of get a little better. They’re still easy, but you couldn’t make a spoiler for your car with them. But, ima