Automate the complete feature engineering and selection process with built-in tools. Harness AutoML to deliver top-performing machine learning models and boost accuracy through automated hyperparameter tuning. Once your model is developed and validated, deploy it instantly with a one-click deployment option.
Automated Data Science Capabilities of NewgenONE Platform
Intelligent Automated Feature Engineering
Advanced AI-driven Feature Selection
Enterprise-grade High-performance AutoML
Automated Model Deployment and Retraining
Intelligent Automated Feature Engineering
- Automatically generate AI-ready features by analyzing relationships across columns, tables, and datasets using AutoML-driven intelligence.
- Create scalable, high-quality features by intelligently handling complex, multi-level relationships between enterprise datasets.
- Apply governed, custom feature rules to align feature engineering with business logic, compliance, and model objectives.
Advanced AI-driven Feature Selection
- Improve model performance using advanced, AI-driven feature selection that intelligently selects from thousands of available features.
- Apply enterprise-grade, automated feature validation based on the selected modeling algorithm to ensure reliable model training.
Enterprise-grade High-performance AutoML
- Achieve optimal model performance with ML automatically selecting the right pre-processing, algorithms, and parameter configurations to scale AI initiatives efficiently across the enterprise.
- Improve model performance with enterprise-grade automated hyperparameter tuning using advanced optimization techniques such as grid search and Bayesian optimization.
- Optimize computational costs by using time-bound AutoML to control resource usage and improve cost efficiency.
Automated Model Deployment and Retraining
- Enable one-click model deployment once AI models are developed and evaluated, accelerating time-to-value.
- Leverage intelligent, automated model retraining and selection based on predefined schedules or event-driven triggers to maintain optimal performance.
Intelligent Automated Feature Engineering
- Automatically generate AI-ready features by analyzing relationships across columns, tables, and datasets using AutoML-driven intelligence.
- Create scalable, high-quality features by intelligently handling complex, multi-level relationships between enterprise datasets.
- Apply governed, custom feature rules to align feature engineering with business logic, compliance, and model objectives.
Advanced AI-driven Feature Selection
- Improve model performance using advanced, AI-driven feature selection that intelligently selects from thousands of available features.
- Apply enterprise-grade, automated feature validation based on the selected modeling algorithm to ensure reliable model training.
Enterprise-grade High-performance AutoML
- Achieve optimal model performance with ML automatically selecting the right pre-processing, algorithms, and parameter configurations to scale AI initiatives efficiently across the enterprise.
- Improve model performance with enterprise-grade automated hyperparameter tuning using advanced optimization techniques such as grid search and Bayesian optimization.
- Optimize computational costs by using time-bound AutoML to control resource usage and improve cost efficiency.
Automated Model Deployment and Retraining
- Enable one-click model deployment once AI models are developed and evaluated, accelerating time-to-value.
- Leverage intelligent, automated model retraining and selection based on predefined schedules or event-driven triggers to maintain optimal performance.