Minitab Model Ops
Operationalize. Bridge the gap between model creation and model production with a simple, yet powerful MLOps platform.
ML Model Lifecycle Management for Everyone
As machine learning use cases grow, the need to deploy and operationalize models has emerged. Minitab Model Ops helps business analysts and engineers successfully implement their own Machine Learning and Predictive models.
- Make Accurate Predictions
- Monitor & Manage
- Govern
Gain Valuable Insights and Improve Outcomes
Gain valuable insights and optimize processes with real-time predictions. Build predictive models in Minitab Statistical Software, then seamlessly deploy them through Minitab Model Ops for on-the-floor use. This feature empowers you to identify key drivers, optimize processes, and make data-driven decisions that improve outcomes across your organization.
View Model Performance From Anywhere
Minitab Model Ops goes beyond basic predictions, offering powerful remote monitoring capabilities to ensure optimal model performance. Track key drift and stability metrics over time to proactively identify any performance degradation. Set critical thresholds for each model to receive real-time alerts when issues arise. Additionally, gain complete transparency into model health with insights into uptime, response times, and overall deployment status. This proactive approach allows you to maintain optimal model performance and ensure the continued accuracy of your predictions.
Trustworthy and Compliant Models
Ensure trust and regulatory compliance with robust governance features built into Minitab Model Ops. Deliver your models securely by controlling access with secure API keys. Track all changes made to models with detailed audit logs, providing a traceable update history. By prioritizing security and governance, Minitab Model Ops enables you to confidently deploy and leverage your powerful predictive models across your organization.
See How Our Clients Use Minitab Model Ops
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