CLAI Ventures Invests in Godela: The Future of Physics-Powered AI for Engineering
At CLAI Ventures, we back breakthroughs at the intersection of AI and climate. Godela, a Stanford-founded startup in Y Combinator’s Spring 2025 cohort, is developing an AI-native physics engine with the potential to replace conventional simulation tools across engineering. We’re thrilled to support co-founders Cinnamon Sipper and Abhijit Pamarty as they reimagine how physical systems are modeled using AI.
A New Interface for Engineering
Today, if you want to stress test a product (e.g. whether it will fail under stress or how it behaves under heat), you either run costly physical tests or simulate it using tools like Ansys, requiring time, expertise, and compute. Godela eliminates those bottlenecks. Using its AI-powered engine, engineers can upload CAD files, ask questions in natural language, and get simulation-quality answers in seconds.
For example, a drag and pressure simulation for an automobile that takes 2.5 hours on Simscale runs in just 1.8 seconds on Godela, a 4500x speedup. They have predicted the Navier-Stokes equation with 99.99% accuracy from 72mb of fluid flow data.
Faster feedback loops drive faster innovation, enabling engineers to explore more designs, test new materials, and iterate in real time. That unlocks massive gains in cost, sustainability, and performance, especially in climate-relevant fields like energy, mobility, aerospace, and materials science.
Physics-Aware AI
While most AI models are trained to approximate behavior, Godela’s system actually learns and respects physical laws. Built on their foundational research from Stanford and tested at Intel, the Godela Frontier Model extracts governing relationships directly from raw simulation or experimental data. It doesn’t just fit curves, it learns symbolic structure.
This allows Godela to solve complex, coupled multiphysics problems - like fluid flow, heat transfer, or structural stress - faster, more robustly, and with far less data than black-box models. Even when data is sparse or noisy, the models remain grounded in physics, ensuring trustworthy, explainable outputs.
We believe this foundation is what gives Godela a sustainable advantage in modeling real world problems. They aren’t trying to improve traditional tools; they’re building a new category: the physics foundation model.
From Academia to Industry: Godela has Early Traction
Cinnamon Sipper and Abhijit Pamarty of Godela’s founding team have deep technical experience, including prior roles at Apple, Google, and Intel. They’re supported by advisors like Stanford mechanical engineering professors Gianluca Iaccarino and Ellen Kuhl.
The company recently signed its first contract to replace Ansys, and is currently in early-stage discussions with organizations including Apple, Amazon, Intel, and the European Space Agency. Industry interest has been strong, with over 200 inquiries following their launch.
Thanks to our Stanford founder network, CLAI Ventures secured a place in a highly competitive round, joining other top-tier investors who recognize Godela’s disruptive potential. Just as protein folding was transformed by AI, we believe physics is next and Godela is at the forefront.
Godela’s models are 4500x faster than legacy tools like Ansys (a $30B market incumbent) and can generalize across physics domains with minimal data. They’re building a foundation model for the physical world, not just a niche solution, and applying it to climate-relevant use cases with clear ROI. Most importantly, the founders bring exceptional credibility, clarity, and execution speed.
Targeting Climate-Linked Markets
What we find most compelling is Godela’s application roadmap: they’re developing tools on top of their core engine to tackle complex, high-impact engineering problems— starting with three markets closely tied to sustainability and climate resilience:
Drop Simulation: A $1.2B packaging and product durability market, where waste and overdesign are rampant. Godela is already piloting with Amazon to reduce packaging waste and improve compliance.
Thermal Reentry: A $1B market in space and aerospace. Modeling reentry conditions accurately can reduce risk, material use, and environmental impact in aerospace engineering.
Soft Materials: A $4–7B market in advanced and flexible materials, where prototyping is costly and slow. Faster modeling accelerates the development of sustainable materials and hardware.
Each of these cases involves complex, nonlinear, and coupled systems where traditional tools struggle and Godela thrives.
The future of simulation is not more solvers, it’s AI that understands physics and gets smarter with every deployment. Godela is building that future, and CLAI Ventures is proud to be part of the journey.