Vinci raises $250 million Series B at a $1.5 billion valuation to build ai-native physics infrastructure for hardware engineering. 12 minutes ago Vinci has raised a $250 million Series B at a $1.5 billion valuation to build an AI-native platform that lets hardware engineers understand how products will behave while they are still being designed. Vinci has announced a $250 million Series B co-led by Advent, Temasek and Xora, with participation from AMD Ventures, Eclipse, Khosla Ventures, Madrona and others, valuing the company at $1.5 billion. Vinci is building an AI-native computational platform intended to widen what hardware engineers can create. It starts with Continuous Physics Reasoning, the ability to understand how a complex product will actually behave while it is still being designed. The company's aim is for engineers to explore far more possibilities, find better designs and eventually create products beyond the reach of today's engineering tools. The new capital will help Vinci build on its initial success in semiconductor physics by covering more physical phenomena, engineering disciplines and hardware industries. Vinci's founding argument is that human imagination has long run ahead of the ability to engineer what is imagined. Turning an idea into a working physical product means navigating huge design spaces, understanding interactions across increasingly complex systems and finding solutions within the limits of physics, materials, manufacturing and technology, and these challenges grow as products become more complex. Vinci's long-term ambition is to remove these barriers by cutting the time, computation and specialist expertise needed to turn an idea into a physical product. Continuous Physics Reasoning: understanding while designing. Continuous Physics Reasoning, Vinci's core product capability, gives engineers deterministic, solver-accurate insight into how a product will behave during design, rather than waiting for isolated simulation checkpoints. The platform is already running on production engineering programmes and analyses manufacturing-scale designs of up to more than 15 billion degrees of freedom in minutes rather than hours or days. "Designing advanced systems requires engineers to understand how thermal, physical and electrical behavior interact across the chip, package and board," said Brian Amick, senior vice president of technology and engineering, AMD. "By bringing fast, accurate simulation into the design process, teams can evaluate tradeoffs earlier, iterate more quickly and make better architectural decisions while there is still time to act. We're excited to support Vinci as it helps bring these capabilities to engineering teams." The capability rests on a new computational architecture that combines automated design understanding and preparation, agentic orchestration, a Foundation Model for Physics and GPU-native physics kernels. Surrogate models have to be trained or tuned for particular designs, geometries or problem classes, but Vinci works zero-shot on new designs with no customer-specific training or fine-tuning. The result, the company says, is deterministic, solver-accurate physics at manufacturing resolution and engineering speed. Vinci has already commercialised Continuous Physics Reasoning across thermal, thermo-mechanical and convective fluid behaviour, beginning in semiconductors, which it describes as one of the most physically demanding engineering environments in the world. At that speed and scale, engineers can use physics differently, exploring far more possibilities, examining tradeoffs and understanding physical consequences while they can still influence the design. Expanding across Physics and engineering. The $250 million will drive Vinci along two dimensions. On the physics side, it plans to widen coverage beyond thermal, thermo-mechanical and convective fluid capabilities towards broad coverage across hardware systems, including memory and advanced computing, vehicles, aircraft and satellites. On the engineering side, it will move beyond showing engineers what will happen and towards helping them decide what should change, orchestrating increasingly complex systems and constraints, and ultimately creating new designs from human intent. Semiconductors are Vinci's first proving ground, not its destination. The same challenge appears wherever complex physical products must be designed across multiple physics, engineering disciplines, suppliers and organisations, and Vinci's long-term goal is to bring a growing share of that accumulated engineering knowledge into a single AI-native system. The round brings together investors with experience across technology, AI, semiconductors, industrial transformation and long-term infrastructure investment. Advent, Temasek and Xora co-led, with participation from AMD Ventures, Madrona, existing investors Eclipse and Khosla Ventures, and others. The company believes the opportunity goes well beyond making today's engineering analysis faster, and that it can sharply reduce the gap between human intent and a physically realisable product. "The complexity of the physical systems the world is building is increasing dramatically, while the computational infrastructure engineers use to understand those systems has not kept pace. Vinci has developed a fundamentally new approach to this problem and has already demonstrated it in some of the world's most demanding engineering environments. We believe Vinci has the potential to become a foundational technology for a new era of hardware engineering," said Alek Ferro, Technology Investor at Advent. "Physics defines the system of truth for the world we live and build in, and its laws dictate almost everything we build. Yet, hardware engineers have been forced to treat simulation as a scarce resource, with every answer costing hours of compute, days of waiting, and a specialist's time. Vinci unshackles the creators from that bottleneck by making physical understanding continuous and almost instantaneous," said Karan Mehandru, managing director at Madrona. "Hardik and the Vinci team have proven that when design and experimentation are tightly coupled with answers grounded in the laws of physics, we not only enable physical designers to operate at the speed of thought, but also unleash a new high-water mark of productivity across the entire supply chain of hardware design." "Leonardo da Vinci imagined the airscrew more than four centuries before the first practical helicopter could be built. The idea existed; the engineering capability to realize it did not," said Dr. Hardik Kabaria, co-founder and CEO of Vinci. "That gap still exists throughout engineering today. Our ambition is to compress it. Vinci is starting by giving engineers the ability to understand physical behavior while they are still designing. From there, we are building toward systems that can identify what should change, bring together increasingly complex engineering domains, and ultimately help engineers create what they could not create before. Continuous Physics Reasoning is where that journey begins." "We backed Vinci on the conviction that embedding intelligence directly into the physics of engineering could fundamentally expand what engineers are able to design and build. Vinci has now turned that thesis into a production platform operating in some of the world's most demanding engineering environments. By making solver-accurate physics continuous in the design process, Vinci lets engineers explore far more possibilities and pursue designs that would previously have been too costly, slow, or complex to evaluate," said Phil Inagaki, Chief Investment Officer at Xora Innovation. "As Vinci expands across physics and engineering disciplines, it is becoming the foundational intelligence layer for the physical world, shortening design cycles, avoiding costly downstream failures, and bringing more ambitious, higher-performing products to market faster."

Vinci has launched production-grade thermo-mechanical simulation capability that predicts warpage in hardware designs, built on what it calls the world's first foundation model for physics. The system analyses how hardware bends, twists and deforms under thermal conditions, working directly from full-resolution designs without manual setup. The Palo Alto-based company's platform delivers simulations up to 1,000 times faster than traditional tools whilst maintaining solver-grade accuracy. In production benchmarks, Vinci completed full thermo-mechanical analysis on manufacturing-resolution models in approximately 30 minutes, handling boards up to 100 × 100 centimetres with features down to 20 microns. The pre-trained model runs securely behind customer firewalls without requiring proprietary data training. Over ten semiconductor companies have independently verified Vinci's results against existing finite element analysis solvers and experimental data.