Building AI’s unified compute layer.

🚀  Mission

AI is powerful - but expensive, fragmented, and locked into a few hardware ecosystems. We believe everyone should have the freedom to build and run AI anywhere, without limits. Our mission: make AI’s compute layer unified, efficient, and accessible to all.

🤔  Problem

After decades working at the world’s largest tech companies, we saw the same barriers everywhere—high costs, complex tools, and closed platforms. These limit AI’s reach to a privileged few, stifling innovation and slowing real-world impact.

💡  What we’re doing about it

We’re building modular and composable infrastructure that simplifies AI development and deployment. Our products—MAX for scalable AI deployment and Mojo for high-performance, Python-compatible development—work together to break barriers, unify compute, and put world-class AI capabilities in the hands of every developer.
Modular and composable infrastructure that simplifies AI development and deployment is what the world needs.

💥  How it started

Chris Lattner & Tim Davis met at Google. Frustrated by AI’s fragmented infrastructure and determined to accelerate AI’s global impact, they founded Modular—a team of top AI infrastructure leaders reinventing accelerated compute so anyone, anywhere can build production-grade AI software.

🧠  Leadership team

Chris Lattner

Co-Founder & CEO

Tim Davis

Co-Founder & President

Mostafa Hagog

VP, Engineering

Kalor Lewis

VP, Finance

Eric Johnson

Product Lead

Mike Edwards

Head of Special Projects

🤝  Backed by the best investors in AI

DFJ Growth
Factory
General Catalyst
Google Ventures
Greylock Partners
SV Angel
USIT Fund

Our goal is as enormous as it is profound. We’re building a different kind of company to achieve this.

We have assembled the best AI software and hardware leaders, and are systematically rebuilding the AI software stack from the ground up.

We’re currently hiring!

Build the future of AI with Modular

View our culture
  • Get started guide

    Install MAX with a few commands and deploy a GenAI model locally.

    Read Guide
  • Browse open models

    500+ models, many optimized for lightning-fast performance

    Browse models