AI for Engineering Knowledge Management
Explore what SolidWorks automation actually looks like in 2026 without writing code. From macros and DriveWorks to AI-powered tools, here is what works today.
·
⏱
5 min read
Michelle Ben-David
Michelle Ben-David is a mechanical engineer and Technion graduate. She served in an IDF elite technology and intelligence unit, where she developed multidisciplinary systems integrating mechanics, electronics, and advanced algorithms. Her engineering background spans robotics, medical devices, and automotive systems.
BOTTOM LINE
SolidWorks automation in 2026 no longer requires coding skills, but there is no single tool that does everything. Native features still lag behind marketing promises, and third-party tools solve narrow problems well.
The biggest opportunity for most engineering teams is not faster macros. It is faster access to the knowledge and past work that already exists inside their organization. AI platforms built specifically for mechanical engineering are closing that gap today, without requiring engineers to change their existing tools or learn to code.
Most mechanical engineers did not get into the profession to write VBA macros. Yet for years, the only way to automate repetitive tasks in SolidWorks was to learn a scripting language, maintain fragile code, or pay a consultant to build custom macros that broke every time the software updated.
The promise of SolidWorks automation has always been appealing: spend less time on repetitive modeling, drawing generation, and file management so you can focus on real engineering problems. But until recently, the gap between what vendors promised and what engineers could actually do without coding remained wide.
In 2026, that gap is finally starting to close. Between SolidWorks' own built-in tools, third-party automation platforms, and purpose-built AI assistants for mechanical engineers, there are now genuine options for engineers who want to automate without touching a line of code. This guide breaks down what actually works, what is still hype, and where each option falls short.
The Traditional SolidWorks Automation Stack
SolidWorks has offered automation features for over a decade, but most of them still require some level of technical setup that goes beyond what a typical mechanical engineer wants to deal with.
SolidWorks Macros remain the most common entry point. They record sequences of actions and replay them, which sounds simple until you need to handle edge cases, variable inputs, or different part configurations. Most recorded macros break the moment geometry changes, and editing them requires VBA or VSTA knowledge that falls outside most ME curricula.
DriveWorksXpress and DriveWorks Solo offer rule-based design automation for configured products. They work well for companies that sell variants of the same product, like custom enclosures or bracket families. But the setup process is significant: you need to define rules, build input forms, and maintain the system as designs evolve. For teams without a dedicated automation specialist, the learning curve often kills adoption.
Task Scheduler handles batch operations like file conversion and printing, but it is limited to predefined tasks and offers no flexibility for custom workflows. Engineers frequently report reliability issues with scheduled tasks failing silently overnight.
The common thread across all these tools is that they were designed for power users, not for the average engineer who just wants to stop doing the same thing twice.
IN PRACTICE
The designs and answers we got from our external consultants were very preliminary. Today we get better answers, faster answers. A wider range of design directions that weren't available to us before. It feels like the world was opened.
Harel Oberman, CEO, Oberman Industrial Designs
What SolidWorks AURA Actually Does Today
Dassault Systemes introduced AURA as a virtual AI companion for SolidWorks users at 3DExperience World 2025. The marketing positioned it as a tool that could generate assemblies from text prompts, accelerate rendering, and learn from your design history.
The reality in 2026 is more modest. AURA functions primarily as a documentation chatbot built on top of a general-purpose language model. It can answer how-to questions about SolidWorks features, search community forums, and retrieve help documentation with source links. Some local AI features like Fastener Recognition, Command Predictor, and Contextual Assistant are available in beta, but none of the headline generative capabilities shown on stage have shipped.
There are also significant access limitations. AURA requires a 3DExperience Connected license, which means the majority of SolidWorks desktop users cannot access it without purchasing new cloud licenses. For organizations running traditional perpetual or subscription desktop licenses, AURA is simply not available.
This matters for engineers evaluating their automation options because it means that SolidWorks' own AI story is still in its early stages. The native toolset has not yet delivered the kind of workflow automation that would meaningfully reduce repetitive work for most users.
Third-Party Automation Tools That Work Without Code
Several third-party tools have stepped in to fill the automation gap that SolidWorks' native features leave open.
CustomTools and similar add-ins provide property management and batch processing without scripting. They let engineers update custom properties across hundreds of files, generate BOMs, and manage revisions through a visual interface. These tools solve real pain points, but they are focused on data management rather than design automation.
Pre-built macro libraries from resellers offer automation scripts that engineers can deploy without writing code themselves. The downside is that these are one-size-fits-all solutions that may not match your specific workflow, and customization still requires scripting knowledge.
Configuration-based approaches using design tables in Excel remain popular for parametric families. Engineers define dimensions and configurations in a spreadsheet, and SolidWorks generates the variants. This works well for simple geometric changes but breaks down when topology needs to change between variants.
The limitation shared by all of these tools is that they automate specific, well-defined tasks. They do not help with the broader engineering workflow challenges like finding relevant past designs, validating calculations, or accessing institutional knowledge. They make SolidWorks faster in narrow contexts, but they do not make engineers smarter across the full design process.
AI-Powered Engineering Automation Beyond the CAD Window
The most significant shift in SolidWorks automation in 2026 is not happening inside the CAD window at all. It is happening in the engineering workflow that surrounds it.
Consider how much of a mechanical engineer's day is spent outside of active modeling: searching for existing parts that might fit a new application, hunting through PDM vaults for past design decisions, running calculations to validate material choices, checking standards and specifications, and answering questions from junior team members about how things were done before.
AI platforms purpose-built for mechanical engineering now address these workflow bottlenecks directly. Leo AI, for example, connects to existing PDM and PLM systems like SolidWorks PDM, Autodesk Vault, PTC Windchill, and Siemens Teamcenter to make organizational knowledge instantly searchable in plain language. Instead of constructing complex search queries or knowing exact file names, engineers describe what they need and get relevant results from their own design history.
This type of automation does not require any coding, any macros, or any changes to existing CAD workflows. It layers intelligence on top of the tools engineers already use, reducing the time spent on information retrieval so more time goes to actual design work.
Choosing the Right Automation Approach for Your Team
Not every engineering team needs the same automation strategy, and the best approach depends on where your team actually loses the most time.
If your primary bottleneck is repetitive modeling of product variants, configuration-based tools like DriveWorks or design tables are the right starting point. They require upfront investment to set up but pay off quickly for companies with high-mix product lines.
If your team struggles with file management, property updates, and batch operations, third-party add-ins like CustomTools or pre-built macro libraries solve those problems with minimal technical overhead.
If the real time sink is information retrieval, finding parts, looking up past decisions, validating engineering data, or transferring knowledge between team members, then an AI-powered knowledge layer like Leo AI addresses the root cause rather than the symptom. This is particularly relevant for teams dealing with legacy data across multiple systems, onboarding new engineers, or working in regulated industries where traceability matters.
The most effective teams in 2026 are combining multiple approaches: using configuration tools for design automation, add-ins for file management, and AI for knowledge retrieval. No single tool covers everything, but the goal is the same across all of them: less time on repetitive work, more time on engineering judgment.
FAQ
See What Leo AI Can Do
Try AI-powered engineering search on your own data.
Leo connects to your PDM and PLM systems to make your engineering knowledge instantly searchable. No coding required.
Schedule a Demo →
#1 New AI Software Globally - G2 2026
Enterprise-grade security
Trusted by world-class engineering teams
See What Leo AI Can Do
Try AI-powered engineering search on your own data.
Leo connects to your PDM and PLM systems to make your engineering knowledge instantly searchable. No coding required.
Schedule a Demo →
#1 New AI Software Globally - G2 2026
Enterprise-grade security
Trusted by world-class engineering teams