Neural Concept lands $100M Series C to speed up AI-first product development
Neural Concept, an AI platform spun out of EPFL and headquartered in Lausanne, has raised $100 million in a Series C round. The company embeds AI in design and simulation workflows so engineering teams can move from months to days on iterations while improving efficiency, safety, and sustainability.
Who's backing it
The round was led by Growth Equity at Goldman Sachs Alternatives, with participation from Forestay Capital, Alven, HTGF, D.E. Shaw Ventures, and Aster Capital. Goldman Sachs Alternatives manages over $500 billion in alternative assets; since 2003 its Growth Equity team has invested more than $13 billion in technology-driven businesses. As of September 30, 2025, Goldman Sachs had approximately $3.5 trillion in assets under supervision globally.
Why this matters for product development teams
This is about compressing the cycle time between concept, simulation, and decision. Neural Concept's approach brings AI directly into CAD/CAE workflows, helping teams explore more design options, get higher-fidelity predictions earlier, and reduce dependency on late-stage testing.
- Faster loops: iterate in days, not months, across aerodynamics, thermals, structural analysis, and more.
- Better outcomes: target efficiency, safety, and sustainability goals with data-driven design choices.
- Scalable adoption: integrate across existing toolchains via partnerships with Nvidia, Siemens, Ansys, Microsoft, and AWS.
Use of funds
- Accelerate product development, including a generative CAD capability planned for early 2026.
- Expand global go-to-market teams to support enterprise rollouts.
- Strengthen the platform as the intelligence layer across engineering systems.
What to do next (practical moves)
- Map early use cases where simulation bottlenecks hurt delivery (e.g., CFD runs, thermal constraints, weight reduction).
- Prepare your data: align geometry formats, simulation histories, and PLM metadata for model training and reuse.
- Pilot within a single product line; set clear success metrics (time saved per iteration, prediction accuracy, defect reduction).
- Plan governance: who approves model outputs, how results flow back into CAD/PLM, and how you track versioning.
- Upskill the team on AI-in-CAD/CAE practices to shorten the learning curve and reduce integration friction. For role-based options, see these AI course paths.
About Neural Concept
Founded in 2019 out of EPFL, Neural Concept serves automotive, aerospace, energy, consumer electronics, semiconductors, and defense. The platform aims to sit natively in design and simulation workflows so teams can scale AI without ripping out existing systems.
Learn more at neuralconcept.com.
Quick facts
- Company: Neural Concept
- Amount Raised: $100.0M
- Round: Series C
- Funding Date: December 2025
- Lead Investor: Goldman Sachs Alternatives
- Additional Investors: Forestay Capital, Alven, HTGF, D.E. Shaw Ventures, Aster Capital
- Software Category: Engineering AI / Product Development Intelligence
- HQ: Lausanne, Switzerland
- Partners: Nvidia, Siemens, Ansys, Microsoft, AWS
Source
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