AI for Engineering Productivity
AI for SolidWorks is changing how engineers design. Learn what AURA handles, where it falls short, and what fills the gap in 2026.
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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 AURA addresses a real but narrow problem: generating new geometry faster. For the 60 to 80 percent of engineering work that involves finding, reusing, and building on existing designs, AURA offers nothing. That gap is where the most engineering hours are lost and where the most money is wasted on redundant parts.
Leo AI fills that gap by making your entire SolidWorks vault searchable by natural language and geometric similarity, while preserving the tribal knowledge behind every design decision. If your team spends more time searching for parts than designing them, the AI layer you need is not a better geometry generator.
You open SolidWorks on Monday morning, and the first thing you need is a mounting bracket from a project your team finished eighteen months ago. You know it exists. You know someone designed it. But SolidWorks PDM returns 400 results for "bracket," and none of the file names tell you which one fits your current constraints. Forty-five minutes later, you start designing a new one from scratch.
This is the daily reality for most SolidWorks users, and it is exactly the kind of problem that AI for SolidWorks should solve. Some of it does. Most of it does not.
What SolidWorks AURA Actually Handles
Dassault Systemes introduced AURA as the AI layer inside SolidWorks. It focuses on geometry generation and design assistance within the active modeling environment. AURA can suggest topology-optimized shapes, help with lightweighting geometry, and assist with assembly suggestions based on the current design context.
For engineers starting a new part from a blank canvas, these capabilities have value. Topology optimization, in particular, has a clear use case in aerospace and automotive applications where shaving grams matters. AURA operates inside the SolidWorks environment, so there is no context switching to a separate application.
But here is the problem: most engineering work is not starting from scratch. Research from Aberdeen Group estimates that 60 to 80 percent of mechanical engineering tasks involve modifying, reusing, or referencing existing designs. The blank-canvas scenario that AURA addresses is the minority of the workload.
IN PRACTICE
What Engineers Are Saying
"The geometry search has been invaluable, helping me find standard parts instead of designing new ones, saving a huge amount of time and effort. The search system is smart and CAD-aware. It was made by people who truly understand the struggles of mechanical engineers."
— Eytan S., R&D Engineer
The Gap AURA Leaves Open: Finding What Already Exists
The biggest time sink in a SolidWorks workflow is not creating geometry. It is finding the right existing part, understanding why it was designed a certain way, and retrieving the engineering context behind past decisions.
Consider what happens when an engineer needs a specific component:
1. They open SolidWorks PDM and search by file name or custom property
2. They scroll through dozens of results with cryptic naming conventions like "BRK-4412-REV-C"
3. They open multiple files to check dimensions, material, and fit
4. They ask a senior colleague who might remember the project
5. If the colleague is unavailable or has left the company, they start over
AURA does not address any of these steps. It has no access to your vault history, no ability to search by geometric similarity, and no way to surface the engineering rationale behind a past design decision. This is not a minor gap. It is the gap that costs engineering teams the most hours every week.
What AI for SolidWorks Should Actually Look Like
A complete AI layer for SolidWorks needs to do more than generate new geometry. It needs to make the thousands of existing designs in your vault accessible, searchable, and reusable.
That means three capabilities that AURA currently lacks:
1. Natural language part search across the vault. Engineers should be able to describe what they need ("12mm stainless steel spacer from the pump housing program") and get accurate results in seconds, not minutes of manual filtering.
2. Geometric similarity matching. When an engineer has a STEP file or a partial design, the AI should identify similar parts already in the system, even if the file names and metadata give no useful clues.
3. Tribal knowledge retrieval. Design decisions, material choices, tolerance rationale, and lessons learned from past projects should be retrievable by any engineer, not locked in emails or in the heads of senior team members who may no longer be with the company.
How Leo AI Fills the SolidWorks AI Gap
Leo AI is built specifically for this problem. It connects directly to SolidWorks PDM and reads native SLDPRT, SLDASM, STEP, and IGES files. It understands actual geometry, not just file names or metadata tags.
When an engineer asks Leo "find me a stainless steel bracket that fits a 40mm bore with M6 mounting holes," Leo searches across the entire vault and returns the closest matches in under ten seconds. It also surfaces the engineering context behind each result: why a particular material was chosen, what tolerances were applied, which project the part originated from.
This is the layer that AURA misses entirely. AURA helps you design something new. Leo helps you find, understand, and reuse what your team has already built. For organizations with vaults containing 10,000 to 100,000+ parts, that distinction saves significant engineering hours every week.
Leo also captures tribal knowledge that would otherwise walk out the door when a senior engineer retires or changes roles. Design decisions, calculation rationale, and project-specific constraints become searchable institutional memory rather than scattered emails and undocumented assumptions.
The Real Cost of Designing What You Already Have
The financial impact of poor part reuse is not theoretical. Industry data shows that engineering teams with over 20,000 parts in their vault carry 15 to 30 percent redundant components. Each redundant part means duplicated design time, additional drawings, separate tooling, unique procurement line items, and inflated BOM costs.
A single custom bracket that could have been replaced by an existing standard part can cost $200 to $500 in unnecessary design and procurement overhead. Multiply that across hundreds of custom parts per year, and the cost to a mid-size engineering team reaches six figures annually.
The fix is not more geometry generation. It is better search, better reuse, and better access to the engineering knowledge that already exists inside your organization. Teams that have adopted AI-powered search for their CAD environments report finding reusable parts in minutes instead of hours.
FAQ
Stop Redesigning Existing Parts
Your vault has the answer. Leo AI finds it.
SolidWorks teams lose hours searching for parts already in their vaults. Leo AI makes your entire PDM searchable by description, geometry, or engineering context.
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