Why surrogate models speed up decisions

An accurate simulation can take hours per run. When you need to explore thousands of options, the cost in time and compute becomes the biggest barrier.

What a surrogate model is

A surrogate model, or proxy, is a machine-learning model trained on the outputs of full simulation runs. Once trained, it can predict the outcome of a new configuration almost instantly, while preserving the trends and logic of the original simulation.

The practical payoff

• It shortens the loop from days to seconds.
• It lets you sweep the whole parameter space instead of a few points.
• It cuts compute cost per decision substantially.

You still need the real simulation

Surrogate models do not replace high-fidelity simulation. They complement it: use the proxy to quickly narrow down good options, then validate with full simulation before the final decision. That balance of speed and trust is exactly what CiviX is built around.