About Modzy

Building a world where people and machines working together—outperform either working alone

Founding story

Modzy was founded with a clear purpose: Build a world where people and machines working together—outperform either working alone.​

We believe accelerating the adoption of AI and machine learning for organizations, big and small, is Modzy fulfilling our purpose. But deploying AI in the real-world is complicated. The Modzy platform helps organizations jump the Machine Learning "Valley of Death", moving great AI models from development into production and creating value--at scale.

Our technical expertise with AI systems and real-world experience implementing large-scale production ML drove the concept for Modzy. Many patents, long hours, and happy users later, we’ve achieved what no one else could: the secure MLOps platform to manage AI at scale.

Modzy team photo in early 2020, building the ModelOps and MLOps software platform for AI

Meet the founders

Leaders of Modzy, the ModelOps and MLOps software platform for AI
Josh Sullivan
CEO & Co-founder
Leaders of Modzy, the ModelOps and MLOps software platform for AI
Josh Elliot
COO & Co-founder
Leaders of Modzy, the ModelOps and MLOps software platform for AI
Seth Clark
Head of Product & Co-founder
Leaders of Modzy, the ModelOps and MLOps software platform for AI
Kirsten Lloyd
Head of GTM & Co-founder

Join the team

Imagine the world that AI will create—then be part of building it

team on stage for Modzy MLOps platform


Latest MLOps resources from Modzy


Tech Talk: Data Labeling for ML Model Retraining with Label Studio
September 26, 2022

Data-centric AI doesn’t just stop with cleaning and preparing data for model training – there are rich insights to be gleaned from…



Choosing the Right MLOps Solution for Your Business
September 13, 2022

White Paper – Evaluating MLOps Solutions Cut through the hype and noise around MLOps solutions with this white paper that breaks down…



Why a Hybrid Approach to MLOps is Best
September 13, 2022

White Paper – Why a Hybrid Approach to MLOps is Best If you’re looking to introduce a modern MLOps capability for your…