Here's what's new in our latest update:
We’ve launched an AI-assisted, zero-setup Python Notebook to streamline scripting, visualization, and post-processing with the Luminary SDK—integrated directly into the application. Skip environment setup and SDK installs; just open the notebook, and you're ready to start coding.
The integrated AI assistant helps generate and complete scripts quickly, while an interactive 3D widget lets you explore simulation results, compare runs, and analyze data without leaving within the platform.
You can access the notebook from the sidebar in the Projects page. Read more about its features and best practices here.
Here's what's new in our latest update:
Here's what's new in our latest update:
Here's what's new in our latest update:
Here's what's new in our latest update:
Here's what's new in our latest update:
You can now click Select All from the contextual right-click menu to select everything in the current view, excluding hidden surfaces.

The Download All button in the Results table now includes additional columns: credits, run time, iterations, date, and run status.
Here's what's new in our latest update:
Note: This feature is currently incompatible with tags.
Tags can now be used as references to volumes for mesh sizing, supporting robust mesh automation pipelines.
We now support integration with OpenCSM, developed by Engineering Sketch Pad. OpenCSM is an open-source CAD package that enables parametric geometry modeling.
Here's what's new in our latest update:
We've released 2D Power Maps, enabling you to apply a spatially varying heat flux boundary condition. Read more here.

Add filters to streamline navigation and simplify views based on data in the Projects and Results tables.

Here's what's new in our latest update:
The Shrinkwrap tool now supports volume subtraction. This is particularly useful for creating clean outer envelopes while omitting internal components or voids.

Here's what's new in our latest release:
We've added support for supersampling in the SDK rendering pipeline. Images are rendered at a higher internal resolution and downsampled using area-based averaging to reduce aliasing.
Without supersampling:

With supersampling:
