About Us

MLOps Driven Machine Learning on Kubernetes

Empowering organizations to rapidly turn data into actionable insight by democratizing machine learning and automating complex workflows.

As machine learning becomes mainstream, more and more organizations run into the same challenges.

The complexity of data science, cloud native infrastructure, frameworks, patterns, and data is ever increasing.

Organizations want to achieve a continuous deployment model for data science just as traditional DevOps has achieved, but there are significant challenges;

  • Fragmented environments: A Data Scientist’s local environment operates very differently to a production cloud environment

  • Disjointed workflows: Data Scientists and Machine Learning Engineers want to work in Jupyter Notebooks, VSCode, and other familiar tools. They are data science experts, not infrastructure or storage specialists

  • Data versioning hell: Machine learning is unique – data, as well as code, is constantly changing, making debugging and collaboration nearly impossible


Reality Of Most Data Science Projects


Projects Fail

Months to Production

Arrikto’s Machine Learning solutions enable data science and machine learning operations teams to collaborate together to continuously build, train, deploy, and serve machine learning models with DevOps efficiency.

Common Integrated Foundation

Go faster with a standardized and consistent environment from your laptop to the cloud with all of your familiar tools, frameworks, and libraries.

Integrated Workflow Automation

Reduce complexity and reliance on DevOps Engineers with push-button code to pipeline and hyperparameter automation. Focus on models, not Docker containers and cloud infrastructure.

Compliant Reproducible Pipelines

Train and debug models collaboratively even as underlying models, code, and data change. Keep track of experiments, 


Making Democratized Intelligence Automation The Reality For Everyone

Model Experimentation and Building

Enable Data Scientists and Machine Learning Engineers to work their way with familiar tools in an integrated ML Studio.

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Train and Serve Models at Scale

Automate rapid deployment from model experimentation to large scale training and serving with the push of a button.



Our Leadership Team

Joe Costello

Joe Costello

Executive Chairman 

Vangelis Koukis

Vangelis Koukis

CTO & Founder

Josh Bottum

Josh Bottum

Vice President Community Relations

Eric Thune

Eric Thune

Vice President Enterprise Sales

Andrew Hatfield

Andrew Hatfield

Vice President of Marketing