A single, production-grade environment for all your SAS, R, Machine Learning, and Regression model needs
Model Catalog
Explore models built and uploaded by your Data Science team, all from one centralized repository.
Model Deployment
Create and scale model deployments in just a few clicks. Deploy models developed in any framework or language.
Model Monitoring
Make better business decisions to save your team time and money. Monitor model performance and detect model decay as it happens.
Model Governance
Spend less time on model validation, bias detection, and internal audit processes. Go from model development to internal auditing to production faster than ever.
Model Management
Manage multivariate models through A/B testing for live inference and batch tasks.
Model Workflow
Apply business logic to your model prediction results. Create workflows for your models using multiple sources and languages.
Built for Enterprises
Automated Model Containerization
Stop one-off work and make your teams more productive. Datatron supports anything you'd build a model with, such as: TensorFlow, H2O, Scikit-Learn, and SAS.
Scalability
Scale Datatron to your organization's needs. Handle increase in data loads from GB's to TB's for tens to thousands of models with ease.
On-Prem, In the Cloud, Hybrid, or Air-Gapped
Whether your infrastructure is designed for on-prem, multi-cloud, or both, Datatron works across AWS, Azure, Google Cloud, as well as on-premises options.
No Model Development Vendor Lock-In
Don't be locked down to proprietary technology (e.g. SAS and MATLAB). Datatron allows you to migrate to open source alternatives for your ML models.
Model Reproducibility
Reliably reproduce model behavior in production without impacting existing traffic. Datatron lets you take debugging offline with features to replicate production data.
Model Bias
Datatron provides monitoring and evidence to quickly show your auditors what steps were taken in production when your models are biased.
