About RunMat
Every generation of engineers has had a tool for doing math. The abacus. The slide rule. The graphing calculator. MATLAB/Fortran.
Each one made calculation faster, enabled larger scale problems, and put it in more hands. Each one has, as a result, enabled new engineering breakthroughs.
At RunMat, our goal is to build the best tool for running math: the best calculator of our generation. If you use computers to run math, we're building RunMat for you.
Our north star is simple: make running math fast, accessible, and collaborative for everyone who uses computers to run math.
Math per second
Calculation speed has always set the ceiling on what we can build. Ancient Egyptian builders used knotted ropes as calculators, managing a few operations a minute to do their calculations, and with that they raised the pyramids. Every advance since, from logarithm tables to the microprocessor, unlocked a new tier of engineering.
The latest advance is the largest: dedicated math hardware. GPUs are in every laptop and desktop, and have made arithmetic almost free, yet most math tools were built for the CPU and treat the GPU as an afterthought. RunMat treats the GPU as a first-class compute device, detecting independent chains of work and dispatching them in parallel to saturate your hardware. The result is the same math, running orders of magnitude faster.
We believe computation speed is the single biggest constraint on what we can build. We want to help you push the limits of what you can do with math.
What RunMat is today
Runtime. At the core is an open-source runtime written in Rust. It executes MATLAB syntax code with a fast-starting virtual machine and a JIT compiler, while an acceleration engine fuses array operations into GPU kernels and keeps data resident on the device between them. The result is math written in simple MATLAB syntax, running blazing fast on Apple, NVIDIA, AMD, and Intel GPUs. It ships with a large standard library and a GPU-accelerated 2D and 3D plotting engine, and it's released under the Apache 2.0 license.
Desktop. RunMat Desktop turns the runtime into a daily driver: a code and notebook editor, interactive GPU-rendered 2D and 3D plots you can orbit and zoom, and a workspace inspector that shows the type, shape, and device residency of every variable as your code runs, and a Codex/Claude Code-class agent harness that's directly seeing your plots and variables as you iterate with it. It can run entirely in the browser, while still running locally rather than on our servers, or can be downloaded and run as a native application on macOS, Linux, and Windows.
Collaboration. Serious math is rarely a solo effort, so RunMat is built for working together. Projects are shared workspaces: when a teammate saves a file, you see the change in real time. Every save is versioned automatically, recording who changed what and when, and a single click captures a snapshot of your whole project so you can always return to a known-good result. There's no version-control ceremony, no "which copy is current," and no emailing files around.
You can dig into how all of this works in the documentation.
Where we're going
RunMat is a platform for running math, and we're building it out in every direction.
We want running math to be effortless at any scale: the same code that runs on your laptop should run on a far bigger machine the moment you need more power, and eventually on the very hardware you're designing for. Scaling up and down should be effortless. We want the hardest parts of high-fidelity work, like simulation and math over real geometry, to feel approachable.
We want to allow anyone to simulate reality in high fidelity, and help you push the limits of what you can do with math.
The team
Nabeel Allana
Self-taught programmer since age seven and a mechatronics engineer by training, Nabeel was a technical lead on Apple's autonomous-vehicle program and has worked across engineering teams at Apple Product Design, Toyota Manufacturing, and BlackBerry before co-founding the company behind RunMat.
Julie Ruiz
Julie co-founded the company behind RunMat and leads the work that turns RunMat into a product people can find, understand, and adopt, drawing on a background in marketing, communications, and strategic accounts.
Jonathan Weiss
Jonathan is a backend and distributed-systems architect who has spent his career building highly scalable infrastructure and data pipelines, from large-scale consumer applications to data-platform connectors.
Fin Watterson
Fin is a technical marketer and storyteller who has spent more than a decade bringing engineering software, industrial technology, and deep-tech products to market across startups, scaleups, and global manufacturing companies.
Get in touch
The fastest way to understand RunMat is to use it: open the browser sandbox and run a script in seconds. The source lives on GitHub, and you can reach the team anytime at team@runmat.com.