MLOps
Stably manage the machine learning lifecycle
Solving the challenges of machine learning development and operation
MLOps stands for machine learning operations and is also referred to as machine learning infrastructure.
Operational issues arise in the development and operations of systems that incorporate machine learning, such as detecting when abnormal data has been fed in as training data and building a mechanism to automatically relearn the data.
DATUM STUDIO provides a system where machine learning can actually run stably in your business operation using cloud services, thereby contributing to the growth of your business.
End-to-End Support Across Machine Learning Development, Deployment, and Monitoring
DATUM STUDIO guides clients through every stage of their machine learning journey — from initial planning to full-scale adoption. We automate the entire ML pipeline, covering model development, performance management, production deployment, monitoring, and ongoing updates.
By automating machine learning operations, AI engineers and data scientists are free to focus on higher-value work — creating an environment where teams can continuously advance their data capabilities and uncover new insights.
Services
DATUM STUDIO with Amazon SageMaker
Support for MLOps infrastructure building using Amazon SageMaker
DATUM STUDIO with MLflow
Building an MLOps infrastructure using the open source platform MLflow
DATUM STUDIO with Microsoft
Leveraging Microsoft data analytics and AI services for MLOps
DATUM STUDIO with Google Cloud
Achieving MLOps with Google Cloud best practices.
Google Cloud is a trademark of Google LLC.
