Continuous Machine Learning

Accelerating Data Science at scale


Continuous Machine Learning (CML) is a set of tools and practices that brings widely used CI/CD process to a Machine Learning workflow.

Using a validated approach to increasing the agility of software development CML helps organizations to integrate MLOps pipelines on top of the their existing technology stack.


for data science

Use GitLab to manage the end-to-end Machine Learning Lifecycle combined with DVC to enable full data, models and code version control and reproducibility

Flexible Deployment Options

Our CML solution can be easily integrated into your existing technology stack with both

On-premise or Cloud-based deployment options

Automated reporting

Auto-generate reports with metrics and plots in each Git Pull Request. Rigorous engineering practices help your team make informed, data-driven decisions.


The AI Academy for you

We can enable programmatic access to your Machine Learning “back-end” by creating automated pipelines (“functions”) that simplify model experimentation and deployment while introducing continuous model performance and retraining 



Scale your ML Initiative



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