The AI boom didn’t just bring excitement—it exposed a painful truth.

Most mechanical engineers are still stuck with tools from the early 2000s. PDMs and PLMs that feel like spreadsheets in disguise. Endless folder trees. Search tools that only work if you already know the part name. AI that looks smart—until it gives you a made-up answer and no source to back it up.

So when a team at Rafael Advanced Defense Systems asked us:
“Why do some AI products win the market, while others disappear as fast as they came?”
—we knew the answer would hit close to home for engineers everywhere.

We’ve studied dozens of AI products that are either winning big or heading for unicorn status. Tools like:

• Cursor and GitHub Copilot – for developers
  
  
  

• Harvey – for lawyers
  
  
  

• Superhuman – for email power users
  
  
  

• Granola – for meeting productivity
  
  
  

And of course, Leo – the AI copilot for mechanical design.

What do the winners have in common? And why is Leo the natural fit for engineers like you?

1. Trust Matters More Than Hype

If engineers don’t trust a tool, they won’t use it.
Cursor and Harvey restrict their training data to verified sources—no Reddit threads or random blog posts. Leo does the same, but with engineering-grade sources: standards, datasheets, and manuals. No hallucinations. No guesses. Every answer can be traced.

Engineers can’t afford “maybe.” Leo gives “here’s the source.”

2. AI Has to Live Inside Your Workflow

No one wants to switch windows or copy-paste between tools.
GitHub Copilot lives in the IDE. Harvey lives in Word. Leo lives where mechanical engineers actually work—in their CAD tools, PDM folders, and Windows directories.

That’s the difference between an assistant you remember and one you rely on.

Leo doesn’t open a new tab. It opens new possibilities—right inside your existing environment.

3. Modality Matters: GPT Doesn’t Understand Geometry

Generic LLMs were built for language, not for design.
They can’t “see” the 3D shapes you’re working with. They don’t understand constraints, part interfaces, or manufacturability. That’s why Leo includes a purpose-built geometry-aware model that interprets CAD data and supports part selection and design review in context.

You don’t design with sentences. You design with shapes. Leo understands both.

4. UX Is Hard, But Workflow Wins

Tools like Granola thrive on elegant UX. But even clunky software like SAP and Windchill gets adopted—if the value is clear.
Leo was designed to be both: simple enough to use in meetings, but deep enough to support critical design decisions, part reuse, and SoW generation.

5. Privacy Isn’t Optional

In aerospace, defense, automotive, or medical—compliance is mandatory.
You can’t use tools that reuse your data. Leo gives each organization its own isolated instance. Nothing is shared, nothing is retained. We’re pursuing SOC2 and other certifications because our customers demand it—and deserve it.

The Takeaway for Engineers

If you’ve felt that GPT can’t be trusted…
If your PDM hasn’t evolved in a decade…
If you're tired of explaining your designs to AI tools that don't "get it"...

Leo was built for you.

We're not just another AI startup. We’re your copilot in design—trained on your world, your data, and your goals.

Tired of legacy tools and generic AI?
Leo is the only AI built for mechanical design—geometry-aware, workflow-integrated, and source-backed.
→ Try Leo Today