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What is AutoML？

Turn raw data into actionable predictive models with a no-code AutoML approach. Automatically uncover key drivers, hidden variable relationships, and causal insights behind critical metrics—so AI doesn’t just deliver results, but explains the decisions that matter.

  • Automated Feature Engineering – Clean and structure data automatically

  • Data Quality Diagnostics – Instantly understand data readiness

  • Automated Model Generation – Faster modeling with auto tuning and ensembling

  • Model Performance Insights – Continuously optimize and improve results

Why Does Manufacturers Need AutoML?

The real challenge in manufacturing is not data availability, but how quickly data can be turned into usable knowledge. With highly variable processes, relying on data scientists to build models from scratch for every problem is slow and hard to scale.

AutoML empowers process experts to directly build and validate models by automatically uncovering key multivariate drivers, transforming tacit, experience-based know-how into reusable and scalable digital assets—turning AI into a true amplifier of manufacturing knowledge.

How to Start Using AutoML？

To get started with AutoML, simply prepare structured data, upload it to the AutoML platform, and define the prediction target and evaluation criteria. The system automatically handles data processing, feature engineering, model selection, and hyperparameter tuning, producing the best-performing models with built-in support for continuous optimization and explainability—enabling users to deploy real-world applications without requiring deep programming expertise.

Automation is One Click Away

How AutoML Works

AutoML turns complex enterprise data into actionable insights. In four steps, it moves from data to decisions—automatically identifying optimal models and key drivers to accelerate real-world deployment.

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Data Processing

Integrate structured data from internal and external sources, and define prediction targets and evaluation metrics.

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Feature Automation

The system automatically performs data cleaning, transformation, and feature generation, while identifying the most influential variables.

 
 
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Automated Modeling

Test multiple algorithms and systematically explore the best model and parameter combinations to achieve optimal performance.

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Decision & Deployment

Provide key driver insights and variable importance, with the ability to deploy applications directly.

Through these four core steps, AutoML enables enterprises to deploy AI models faster and at lower cost, while ensuring results are explainable, deployable, and continuously optimized—truly turning data into decision value.

 
 

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