Prediction and Optimisation Runtime

The Prediction and Optimisation Run-time component in the i4 platform integrates data processing algorithms, provides an API for accessing embedded algorithms, supports multiple instances, and utilizes Docker containers. Users can search for algorithms, adapt or create new ones, embed them in the run-time, and configure and utilize them throughout the AI Analytics Run-time component. The component includes a Gunicorn Server, Redis and MongoDB databases, and allows algorithms to be developed independently and injected using a Docker parent image.


The main advantages of deploying a data processing algorithm as a PO Run-time:

  • Seamless integration into the ZDMP platform. The main benefits are:
  • Efficient development to deployment in ZDMP platform
    • Easily access data published on the ZDMP platform
    • Share data processing results with components/zApps on the ZDMP platform
  • Standardised API which allows existing components/zApps to use the newly published algorithms
  • Application Run time providing Minizdmp platform that allows to deploy PO Run-time component locally.
Play Video

Data source selection

Output source selection

Continuous or one-time calculation

Modification of algorithm parameters

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

Get a better understanding of the global architecture and information flow.

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.