WOLFRAM

Augment AI with System Modeler

System Modeler Skills

A bundle of skills that lets Claude Code, Codex or any LLM assistant work with System Modeler directly. More

The assistant drives the System Modeler kernel—creating, validating, simulating, diagnosing, plotting and documenting real models. Skills also cover the system modeling functions in Wolfram Language, enabling you to do unlimited analysis.Less


Create

Let your AI Assistant build Modelica libraries—with reusable components, validated at every step and simulated to catch runtime errors.More

Validated models come fully rendered with icons, laid-out schematics and embedded result plots, so you can review them at a glance.Less


Diagnose

Let your AI assistant look inside the model—equation blocks, initialization equations, the flattened code—to pinpoint what’s wrong and why.More

Trace how any variable is solved and get the simplified equations in human-readable form.Less


Post-Process

Go from simulation to insight automatically—use the system modeling functions in Wolfram Language. More

Design controllers, optimize control trajectories, run Monte Carlo simulations and validate against design requirements.Less


Knowledge-Backed Answers

Get authoritative answers from the full Modelica Language Specification, the Modelica Standard Library and the System Modeler documentation.More

Every answer cited to its source, so you can verify it.Less


Physics Models with Neural Nets

Embed trained neural networks directly into your system models.More

Learn unmodeled physics from measurement data, replace hard-to-characterize components with data-driven surrogates and keep first principles and machine learning in a single model.Less


Fast Surrogates

Distill complex system models into lightweight neural surrogates that run in milliseconds.More

They deploy easily, making them ideal for rapid design exploration, cloud applications and optimization tasks.Less


Reinforcement Learning

Turn your system model into a safe, simulated training environment for reinforcement learning.More

Explore aggressive control strategies and failure cases in simulation, before anything touches real hardware.Less