Leading Generative Design Company nTopology Gets $65 Million Booster Shot

What will they do with all that money? We find out.

Will wonders never cease? nTopology uses multiphysics in generative design of this non-pneumatic tire. (Picture courtesy of nTopology )

Will wonders never cease? nTopology uses multiphysics in generative design of a non-pneumatic tire. (Picture courtesy of nTopology )

The company with a weird name just got closer to making its name a household word. nTopology just announced that it has received funding of $65 million, almost doubling the $70 million it has already received. Let’s put that in perspective. It’s about half of what Onshape, the most anticipated CAD startup ever, raised in venture capital. It is many times what Shapr3D—what may be the easiest-to-use CAD ever—has raised (about $12 million).

That’s what I’m talking about. Bradley Rothenberg, CEO and cofounder of nTopology, with one of his optimized shapes. (Picture courtesy of nTopology.)

That’s what I’m talking about. Bradley Rothenberg, CEO and cofounder of nTopology, with one of his optimized shapes. (Picture courtesy of nTopology.)

nTopology was created as an alternate to CAD, which cofounder and CEO Bradley Rothenberg says is of little help in the design process.

“Earlier in my career, I found that most of the engineering software, like CAD, was a bottleneck in driving innovative design. Our company was built specifically to solve engineers’ problems, allowing them to fully utilize the power of additive manufacturing processes and fill the gaps left by these old legacy design tools,” said Rothenberg in the press release.

The funding boost comes after nTopology has created a business with 300 customers, including such industrial heavyweights as Ford, Lockheed Martin, Honeywell and Emerson, and has seen its revenue double, according to company literature. Further details of revenue and profit are not forthcoming, but that is typical of startups at this stage—they are flush with funds and are more concerned with growth than profit.

Design, solve, repeat. Topology optimization iterates through design and simulation—repeatedly and automatically—until a part is as simple as possible—but no simpler. At least theoretically. (Picture courtesy of nTopology.)

Design, solve, repeat. Topology optimization iterates through design and simulation—repeatedly and automatically—until a part is as simple as possible—but no simpler. At least theoretically. (Picture courtesy of nTopology.)

We called Rothenberg last week to congratulate him. We found him getting ready to attend Formnext, the 3D printing tradeshow in Frankfurt.

Where are you planning to take  your company now?

We’re going the create more applications of our technology. Rothenberg responded after making sure that we had sworn to secrecy before the company’s official announcement.

The plan has always been to build the software that powers the next generation of products. We’re going to continue doing that. Along the way, we have found a set of applications where our software really performs well, like lightweight heat exchangers, design for additive manufacturing, industrial design, etc. Over the next couple of years, we will expand the applications that our software can most benefit.

How important was it for your recent investors that you already had customers and a business, not just an idea and a technology?

It was 100% important. It’s difficult to raise funds with just an idea.

Will nTopology be getting more into fluid flow?

The physics we apply is equally capable of optimizing for fluids as it is for mechanical parts.

We’ve done more work on fluid flow since we last spoke.

Rothenberg had shown us nTopology’s fluid flow after we whined about the lack of fluid flow optimization in the industry. “We can do that,” he said.

What We Think

“nTop,” as it is people in the company refer to it, is well known to engineering.com readers. We have followed the company from its early days, sitting enthralled at demos and conversations with Rothenberg, sharing a common belief that computers need to assist engineers with their designs.

nTopology is borne of that belief. But from decades of covering technology for engineering, we know it takes more than belief, more than genius … it takes marketing, sales … and money.

nTopology has perhaps the most advanced optimization routines on the planet. The big CAD vendors would get a boost in their attempts to generatively design by acquiring nTopology. Like PTC did with Frustum, a generative design company, acquiring it for $70 million in 2018.

This is not a path Rothenberg is interested in. Technology improvement by acquisition is a tired story featuring a promising, ground-breaking technology absorbed into a larger company—maybe never heard from again—its voice lost among louder voices.
And so, a rapid advance of a radical idea slows down to an incremental implementation in the larger company’s portfolio.

Rothenberg wants no less than a transformation in the way software assists us in designing—and staying independent, staying the CEO rather than becoming another VP in a bigger company—leaves him in full control of the company’s destiny—and with a shot at the next big thing in design and simulation.

Unfettered leadership could allow Rothenberg to fulfill the promise of CAD.

We write a lot about what CAD can do—and about what it cannot. It cannot make organic shapes, it cannot optimize, it cannot handle the variety of geometry (points, meshes, irregularities). It cannot do what nature can do—not even close.

Can your lightweighting app duplicate natural bone formation? An AM optimized hip implant stem designed in Ti-6Al-4V. It was the winner of the 2020 Additive World student category DfAM challenge. (Picture courtesy of nTopology.)

Can your lightweighting app duplicate natural bone formation? An AM optimized hip implant stem designed in Ti-6Al-4V. It was the winner of the 2020 Additive World student category DfAM challenge. (Picture courtesy of nTopology.)

Why can’t our lightweight structures be like nature can make them?
This was the subject of discussion over breakfast at the 2018 ASSESS conference
in Atlanta. I’m using my favorite example, the human femur. I am sketching a
section of the femur, trying to show what our bones have formed so naturally and
easily. They are hard on the outside, and on the inside, they have a lightweight
construction of irregularly shaped cells that vary in size, going from hardly
visible at the outside and spacious toward the middle. The conference attracted
a bevy of startups all eager to show their generative design and lightweighting
solutions, all of them with the ability to optimize solid shapes, some able to
make hollow shapes (with lattices), but none could make anything like our bones.
All except one. At our table was Bradley Rothenberg.

“We can do that,” he said.

Can your topology optimization do that? A passive heat sink in copper. (Picture courtesy of nTopology.)

Can your topology optimization do this? A passive heat sink in copper. (Picture courtesy of nTopology.)

Rothenberg’s education as an architect (Bachelor in Architecture, Pratt Institute) may not have prepared him for product design and simulation but may have freed him from the commonplace tedium of the design-simulation sequence prevalent in mechanical design. Dominated by the Big Four (Autodesk, Dassault SysteÌ€mes, PTC and Siemens) on the design side and Ansys on the simulation side, we have gotten quite used to a two-step approach with design first, followed by analysis.
The industry’s only process improvement has been to gain marginal efficiency by uniting products under one roof, making data transfer cleaner between designers and analysts. But the process remains
the same: linear, iterative and manual.

Combining both design and simulation, done back and forth, automatically by a computer and taking the human out of the loop is what generative design aims to do.

nTopology, like most topology optimization programs, is not limited to structurally sound parts. It is one of the few optimization programs that can also deal with optimization of fluid flow, making nTopology more of a general-purpose optimizer. We see optimization of fluid flow as more necessary than structural optimization because the former is less intuitive. Our intuition of structural part failure has developed from being able to see failures (example: fracture) in parts, whereas we can’t see flow failures (example: flow going from laminar to turbulent around an aircraft wing section). Yet, few design software companies offer generative design for fluid flow. (Dassault SysteÌ€mes is one we have covered here
Can You Use Generative Design for Internal Fluid Flow?).

We give our full support to nTopology in holding computer-aided design accountable to its promise by incorporating simulation.