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 Built for Enterprise-scale AI

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.

Standardize and Scale Machine Learning with Automated Data Science on NewgenONE

Accelerate and standardize model development by automating feature engineering, optimization, and deployment, helping data teams deliver production-ready models with consistency and confidence.

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