Neural Concept has secured a transformative €85 million Series C funding round that positions the Lausanne-based AI engineering platform among Europe’s most significant technology investments this year. The round was led by Growth Equity at Goldman Sachs Alternatives, with participation from existing investors including Forestay Capital, Alven, HTGF, D.E. Shaw Ventures, and Aster Capital, demonstrating strong confidence in the company’s innovative approach to AI-driven engineering solutions.
Goldman Sachs heads huge funding round for AI platform
Neural Concept also announced that it has secured funding in the tune of 85 million euros, which is considered one of the largest investments made in an AI platform within Europe during the year 2025. The organization has also managed to register a fourfold increase in revenue from the enterprise segment over a span of 18 months, thereby attracting over 50 firms from around the world, including General Motors, General Electric, Vernova, Leonardo Aerospace, Eaton, Safran, and Renault Group, among other Formula One racing teams, to its innovative platform.
The technology offers CAD native, physics-aware AI and deep reasoning capabilities, reducing costs for customers by $50 million every year, as it cuts down on last-stage redesigns by 30 to 50% and shortens time-to-market by as much as two years. Incorporated in 2019 and born out of collaboration with the Swiss Federal Institute of Technology in Lausanne, Neural Concept offers AI-driven engineering solutions for industries such as automotive, aerospace, energy, semiconductors, and the defense industries.
European AI platform industry garners considerable investment attention
As of 2025, the total European AI platforms operating in ancillary sectors related to the field of engineering intelligence have cumulatively attracted approximately €386 million of publicly disclosed funds, while the Series C of €85 million raised by the firm Neural Concept is one of the larger investments in the European market this year, particularly at the upper end of the scale of investments in AI platforms within the domain of industrial engineering applications.
Key factors influencing the adoption of artificial intelligence in organizations
Neural Concept enables a paradigm shift in engineering by introducing CAD-native enterprise AI that understands geometry, constraints, and design intent to evaluate millions of designs in order to exclude high-end design changes. The group plans to utilize the capital raised to accelerate their product development roadmap, including the launch of their revolutionary generative CAD capability in early 2026, and strengthening collaboration agreements with leading companies such as Nvidia, Siemens, Ansys, Microsoft, and AWS.
Thus, according to a comment from Lambert Diacono, of Next Champions Capital Investment Firm: “The important thing is that this is a breakthrough from an enterprise standpoint regarding AI engineering because there is a clear and growing need for AI that can deliver real-world results.” Again, this specific investment can be viewed from the standpoint that there is a growing need for AI that can provide real-world results, and that Neural Concept is a frontrunner regarding AI-engineering from an enterprise standpoint.
Passes itself off as the intelligence layer of engineering teams worldwide
The purpose for which “We founded Neural Concept was to achieve the goal of completely designing next-generation systems through AI assistance for next-generation cars and space vehicles,” said Dr. Pierre Baque, CEO and founder at Neural Concept. This development in “AI is shifting engineering work from trial and error to data work, thereby allowing engineers to optimize constraints right from the inception process.”
This investment move enables Neural Concept to expedite its pace towards establishing the intelligence layer for every engineering team worldwide and enhancing go-to-market teams worldwide in the engineering systems field. This investment brings the company to the threshold of a rising demand for AI solutions, which in turn helps convert the engineering domain into a business process fueled by data.
