Model Cards
Train, manage, and deploy ML models for predictions and workflows
6
Total Models
4
Ready
1
Training
4
Deployed
Predicts the likelihood of customer churn based on engagement patterns, transaction history, and support interactions.
Accuracy
94.0%
F1 Score
90.0%
Recommends the optimal next action for sales representatives based on customer profile and interaction history.
Accuracy
87.0%
F1 Score
83.0%
Time-series forecasting model for predicting quarterly revenue based on historical trends and market indicators.
Clusters customers into distinct segments based on behavior, demographics, and value metrics for targeted marketing.
Accuracy
88.0%
Scores incoming leads based on their likelihood to convert, helping prioritize sales efforts.
R² Score
91.0%
RMSE
0.120
Collaborative filtering model that recommends products based on customer preferences and similar customer behavior.