The Generative Engineering Platform enables you to run explorations and optimisations over models of your engineering systems. This includes anything, from functions that create geometry and simulate performance, to functions that mimic scientific experiments. Your models can be in Python or in any existing engineering software that we’ve got connectors for.

If you haven’t already, sign up for an account at generative.vision.

In the app, you can set up and run experiments, explore and discover insights from data, find tradeoffs and create comparisons from the generated data.

This documentation will take you through creating models to be used in the Generative Engineering Platform.

​
Key terminology

  • A Generative Function is a model that can be used to generate data in the app. This model can be:

    • A Python function
    • One or more file in one of the external software tools that we’ve got connectors for

  • Generative Functions have inputs and outputs that can be controlled and measured. For Python functions, these are often structured as Generative Types.

  • An Experiment in the app involves running a Generative Function one or more times whilst varying the inputs, to explore or optimise the designs.