US-based software company Vinci secures a Series B round to help engineers early enough how their designs behave, with a technology based on physics intelligence.
The funding round is led by by Advent, Temasek and Xora Innovation, with participation from AMD, Eclipse, Khosla Ventures, Madrona and others, at a $1.5 billion valuation.
From stealth to unicorn in under a year
Vinci was founded in 2023 by Hardik Kabaria (CEO) and Sarah Osentoski. Kabaria holds a Stanford PhD in mechanics and computation, with doctoral work on automating high-fidelity meshing. Before VINCI, Kabaria led software engineering at Carbon, where he worked alongside design teams at companies such as Ford and Specialized Bicycle Components.
On the other hand, Osentoski’s background lies in large-scale machine learning and autonomous systems.
The company came out of stealth in December 2025 with $46 million raised across a seed round led by Eclipse and a Series A led by Xora.
Physics arrives too late
According to Vinci, “for decades, engineers have worked around the scarcity of physical understanding. They ration analysis, narrow the possibilities they explore, and commit to decisions before they know the consequences. Entire workflows have been built around waiting for answers.”
In a blog post, Kabaria explains that: “When every answer requires substantial preparation, compute and specialist time, teams have to decide which questions are worth asking.” The result is safety margins, overdesign and ideas left unexplored.
To address this gap, the team develops Continuous Physics Reasoning, which makes “deterministic, solver-accurate physical understanding continuously available as designs evolve.”
The platform works directly on design geometry without manual meshing or defeaturing, pairs a physics foundation model with established solvers as quality control, and requires no customer-specific training.
According to the company, it can analyze designs with more than 15 billion degrees of freedom in minutes across thermal, thermo-mechanical and convective fluid physics. It already runs on more than 40 flagship production engineering programs at leading semiconductor and electronics companies.
A proven area where AM matters
Semiconductors are Vinci’s “proving ground”, but “the ambition reaches everything we build.” The new funding will extend the platform to more physics, vibration and electromagnetics among them, and to sectors such as vehicles, aircraft and satellites. As Kabaria puts it: “If it is matter, and you can touch it, Vinci can apply.”
Lattices, topology-optimized brackets, consolidated assemblies and conformal cooling channels are exactly the geometries that strain conventional simulation. They are difficult to mesh, costly to solve, and often simplified before analysis, sometimes erasing the very features that make them valuable. A mesh-free approach working on full-fidelity geometry could let engineers evaluate many more design variants instead of rationing analysis to a handful.
Thermal and thermo-mechanical behavior, Vinci’s current strengths, also sit at the heart of many AM applications, such as heat exchangers and cold plates. Continuous feedback could help engineers trim overdesign and back AM-specific geometries with data OEMs can trust.
Interesting fact: Vinci does not currently position its platform as an AM process simulation tool that predicts distortion or residual stress during the build. Its value today lies upstream, in understanding how a part will perform.
Kabaria sums up the ambition simply: “Engineers should be able to pursue an idea because they can investigate it, understand its constraints and improve it.”
That’s I believe a vision worth following closely.
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