🗞️ Highlights Our solver now supports inflow and outflow boundary conditions, allowing us to...
Accelerated mesh generation and multiphysics simulation for complex geometries
With a focus on heat exchangers designed for additive manufacture
Sign up for beta access
A next-generation physics solver
We are building a new physics simulation solver written from the ground up integrating novel machine learning research and modern numerical programming approaches. Deployed through a web application and API gateway.
Featuring:
- Order of magnitude efficiency gains
- Native deployment to cutting-edge hardware accelerators: GPUs, TPUs
- Adjoint methods for arbitrary optimisation targets
Expensive simulations bottleneck product development
To reduce reliance on expensive physical testing, engineers lean heavily on physics simulations to optimise their designs. However, many design problems across aerospace, manufacturing and integrated circuits are extremely computationally expensive to simulate, taking from hours to days to run; critically slowing product development.
By developing an order of magnitude more efficient physics solver, we will dramatically increase the productivity of engineers. This will allow engineers to efficiently search for optimal designs and therefore develop better products.
The Team
Our team combines deep expertise across applied math, machine learning and software engineering.
Laurence Cullen
CEO
Previously: Fetch.ai, Sensity, ARM
Laurence is a machine learning engineer of 6 years skilled at rapid prototyping and has driven two startups to seed as a first and second employee.
Whilst at Sensity, he led the development of one of the world’s first deepfake detection products from scratch, defining and implementing features in consultation with customers from Reuters and The Guardian. He leads on software design, machine learning and commercialisation.
Dr Michael Negus
CTO
Previously: University of Oxford, Diamond
Michael holds a PhD in Applied Mathematics from the University of Oxford, focused on fusing numerical and analytical methods for modelling droplet impacts.
His expertise lies at the interface between mathematics, physics and scientific computing.
He leads the development of our core accelerated physics solver.
Reidmen Arostica Computational Mathematician
Previously: University of Groningen
Reidmen Arostica joins us from his PhD where he used fluid-structure interaction modelling to simulate the dynamics of heart contraction.
Oscar Holroyd
Computational Mathematician
Currently: University of Warwick
Oscar joins us part-time while finishing his PhD at the University of Warwick on thin film fluid control. He is contributing to developing our core solver with his deep range of programming and mathematical skills.
Backed by
About us
Laurence and Michael met at the particle accelerator Diamond Light Source as summer students in 2016, and have been friends since. They moved in together to found Vanellus in the summer of 2022.
They kicked off the business by going through Entrepreneur First, going on to raise a preseed investment round in 2023.
Aditi joined the team in September 2023, and we are hard at work building out our core physics solver, targeting a beta launch later this year.