Rewiring Engineering: How Neural Concept Is Building the AI Intelligence Layer for Manufacturing 

Neural Concept develops AI driven engineering software that enables industrial companies to design and optimise products faster. The Lausanne-based company, an HTGF portfolio company since its seed stage, recently closed a USD 100 million Series C round led by Growth Equity at Goldman Sachs Alternatives to accelerate the global expansion of its AI-native engineering platform. In our interview, founder and CEO Pierre Baqué shares how AI is redefining engineering and what it takes to build a global deep tech champion from Europe.

Pierre, when you meet someone who has never heard of Neural Concept, how do you explain what you do in a few sentences? 

I usually start with the status quo in industry. Today, all advanced manufacturing companies rely on what I call the digital layer. These include simulation and 3D CAD tools that virtualize product development. Engineers design products, run simulations, analyse results and decide what to do next, all inside this virtual environment. 

But even though everything is digital, it’s still humans driving most of the actions and decisions: drawing in 3D, launching simulations, interpreting results. 

What we are building with Neural Concept is the intelligence layer on top of that digital layer. This layer drives the virtual environment and creates a new type of interface with these tools, one that is AI-augmented and AI-driven. It augments engineers, but ultimately it augments entire engineering organisations. 

In short: we’re adding intelligence on top of the digital tools that already run modern product development. 

AI and product development are evolving rapidly. Which developments are you watching most closely? And where do you see the biggest opportunities for Neural Concept? 

I think all developments around AI agents for code and software development will have a tremendous impact on the software industry, and also on software for engineering, which is where we operate. 

I believe everyone is still underestimating how big this impact will be. There has been some turbulence in the market recently, but this is really just the beginning. 

What this means for our space is that many very large incumbents currently control the digital layer, the traditional CAD and simulation tools. With AI entering the equation, the cards will be reshuffled for the next generation of engineering software. 

For new companies like ours, this is incredibly exciting. It’s a moment where you can rethink how value is created for customers and imagine entirely new ways of working. That’s a rare window of opportunity. 

Can you share a concrete example that illustrates the impact Neural Concept has on day-to-day engineering work? 

A good public example is our work with MAHLE, the German automotive supplier. They’ve been using our technology for some time now. 

One result was achieving unprecedented product performance. For example, when designing blower fans used inside electric vehicles, they were able to significantly reduce noise levels, making them best-in-class in the market by a wide margin. This matters a lot, because in electric cars you can hear these components much more clearly than in combustion vehicles. A quieter fan directly improves perceived vehicle quality. 

But beyond performance gains, the real shift is in the process itself. MAHLE is establishing a new development process around AI. They can now reduce development effort and respond much faster to specific requests from automotive OEMs. 

So it’s not just about better products. It’s about faster iteration, more flexibility and a fundamentally different way of engineering. 

You recently closed a USD 100 million Series C funding round led by Growth Equity at Goldman Sachs. What does this milestone mean for you and the company? 

It’s a very exciting time, not only for us, but for technology in general. This round is really fuel for us to position Neural Concept as one of the companies that will redefine our market. More than an achievement, I see it as an opportunity to build something that will be remembered and that will shape how engineering is done in the future. And that’s the mindset we have going forward. 

HTGF has supported Neural Concept from the seed stage as one of the first institutional investors, participating in every financing round. How would you describe our role on your journey? 

HTGF has been an amazing and trusted partner for us. They’ve found the right balance between support and challenge, being there during more difficult times and sharing success with us as well. 

What differentiates them for me is their breadth of exposure to the startup ecosystem. Through HTGF, and especially through Gregor, our investment manager, we have access to a very broad view of what’s happening across many companies and technologies. 

As you grow, you often lose some visibility on early-stage developments and emerging startups. Having someone who sees the bigger picture and can act as a channel of information is extremely valuable. It helps us stay connected to what’s happening in the ecosystem. 

Looking back on your own journey, from researcher to founder and scale-up CEO, what key lessons would you share with deep tech founders just starting out? 

One important lesson is that at some point, you have to accept forgetting about the technology, at least for a while. 

When you start as a deep tech founder, you naturally think about how to push your technology into the market. But eventually you need to flip that perspective. You have to look first at the market and ask: What does this market actually need? What problems do customers really have? 

Only then should you think about how your technology can solve those needs. 

This shift can be uncomfortable. In the beginning, your technology feels like your main asset. When you start focusing on the market instead, you might feel like you’re losing that asset. But in reality, your technology is still there. It just becomes a tool to solve real problems rather than the starting point. 

Another lesson is commitment. Building a company is not something you can do at 90 percent. It really requires going all in, 100 percent. That level of focus and dedication is necessary. 

And finally, you need to understand that business is business. Coming from research, you may initially see the world differently. But you have to learn how competition works, how companies operate and how markets function. That understanding is essential to building something that lasts. 

How do you see the deep tech and VC landscape in Europe today compared to when you started? 

It’s difficult for me to answer completely objectively because I’m no longer an early-stage founder myself. But from what I can see, there is definitely funding available in Europe. 

You may not always see the very large, early-stage funding rounds that happen in the U.S., but if you build a strong company, show ambition and aim to win globally, you can find the capital you need in Europe. The ecosystem is there. 

What’s also changing is the speed of development. With new AI tools and coding assistants, reaching a minimum viable product is becoming faster and easier. That’s great for founders, but it also means that other factors will become more important: distribution, network, product experience and execution. 

Competition will likely increase, but so will the speed of innovation. For ambitious founders, that creates real opportunity. 

Thank you, Pierre, for sharing these inspiring insights!