Physics & AI
Physics & AI combines state-of-the-art machine learning with physics simulation.
AI-based simulators responds to your input in real-time, which means interactive visualization.
No need to install anything or be limited to specific platforms. Everything happens through web interface.
Painless scalability
Painless scalability
Our platform deals with the complexities of setting up cloud or HPC infrastructure for you. title
Software platform
for high-performance
AI-based numerical simulators.
Vast majority of technologies in the world come to life through months or years of extensive simulation during their development.

High-performance computing, parallel processing and GPUs helped push the computation time from months to weeks. With the help of applied machine learning, we are seeing a reduction from weeks to days. We think that's not enough.

At DimensionLab, we are building tools for engineers and researchers to tame the physics of their projects in hours. Collectively, they make up a cohesive platform we call

Under the hood, consists of two parts - Model Engineer and Simulation Studio.

Model Engineer

Train and optimize extremely fast physics simulators using deep learning techniques through web-based Model Engineer application.

Datasets management

Construct large datasets from classical simulation exports or physical sensors that collect precise measurements from real-world experiments.

Building blocks

Quickly develop the model architecture for the simulators's desired capabilities and physical constraints. Customizable to the bone through code editor.

High performance computing, automated

One-click A100 GPUs. Train and aggressively optimize learnable simulators in high-performance, GPU-powered cloud or HPC centers without the need to deal with the complexities of managing the cloud infrastructure.

Simulation Studio

Leverage trained AI simulator models for solving engineering and scientific problems, by constructing interactive, physics and data-driven digital twins.


Simulations are computed by inferring trained neural network models, achieving speedups of 1,000-100,000x compared to classical simulation software running on GPUs.

Interactive "in-situ" visualization

The time it takes to compute one timestep even of highly irregular simulation domain is in low tens of milliseconds, resulting in real-time visualization of simulating physical phenomena.

Unreal rendering performance

High-fidelity visualization rendering is achieved by leveraging the powerful Unreal Engine under the hood.
We believe in the democratization of scientific-grade simulation tools by making it easy for anyone to develop physics-based simulations and deploy them in their workflows, regardless of their technical skills.

Join our community Discord server!

We are giving out free 1 month discounts to early adopters - ask around in our community Discord!


Interested in funding us?

Drop us an email and we will send you our pitchdeck.