AI Analytics Designer

Data analytics plays a key role in the ZDMP architecture with many expected use cases dependent upon it. The AI-Analytics Designer component deals with machine learning integration into ZDMP. The main purpose of machine learning in ZDMP is to detect and/or predict any defects in the production process and parts that lead to delay or inconsistency in the delivery of further products. The machine learning models are built using analytic algorithms based on the statistical-machine-learning linear-algebra libraries.


  • Build machine learning scripts, train, and apply a machine learning model

  • Automate machine learning workflow, which includes automatic training and tuning of many models within a user-specified time limit.

  • Use AutoML to produce highly predictive ensemble models

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Design learning model

This component allows users to build machine learning scripts, train models, and apply them. It integrates with other components through a REST API and includes features such as secure installation integration, storage integration for dataset retrieval and model file uploading, user interface management, and preparation of meta-information for AI Runtime.


AutoML automates the machine learning workflow by automatically training and tuning various models within a specified time limit. It creates stacked ensembles based on previously trained models and the best models of each family, resulting in highly predictive ensemble models. This component generates tasks for model training, builds machine learning models, creates MOJO/POJO files for AI Runtime, and provides information for AI Designer’s chart functionality.

Secure Installation integration

This component adds a security layer over model training in the AI Designer, ensuring secure processes and protecting sensitive data.

Storage integration

The Storage component enables AI Designer to retrieve datasets required for model training and upload model files (MOJO/POJO) to be accessed by other components. It facilitates efficient data storage and retrieval for seamless integration within the ZDMP framework.

Additional resources

Learn more about i4FS by visting the project website for general information, the wiki for information about the core components, the Technical Manual for API documentation, and downloading the repository’s source code.

Training Academy

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Source code

Our source code is opensource and available on our Gitlab repository.

Software Documentation

Read our easy to follow documentation to learn how to use the i4 Components.

Software Tutorials

Follow our step by step tutorials to create your first zApp.