Multi-agent simulation for policy & crisis prediction - WorldSim

WorldSim automatically generates parallel societies from real‑world data Each AI agent has independent personality, memory, and social relationships. It supports multi‑domain coupling — social media, economy, policy, and epidemics — to capture complex real‑world interactions. The platform delivers emergence‑based predictions, counterfactual analysis, and causal inference for policy makers, researchers, and crisis managers.

getviktor.com — An AI coworker that actually does the work

An AI coworker that actually does the work

As a researcher in computational social science, I saw the same problem again and again: governments and organizations wanted to test policies or predict crisis outcomes, but existing simulation tools were either too simplistic (simple equation‑based models) or required months of manual agent programming. I founded WorldSim to change that. The first prototype only simulated opinion dynamics on social media with a few hundred agents. Then we added economic behavior, then policy response, then disease spread — and realized the real power comes from multi‑domain coupling. The hardest part was giving each agent persistent memory and personality without blowing up compute costs. Today, WorldSim can generate a parallel society of 1M+ agents from any real‑world event or policy document, run multi‑domain simulations, and output a prediction report with counterfactual scenarios. We’re launching in private beta for researchers and policy advisors. Join the waitlist to be among the first to simulate the future.

getviktor.com — An AI coworker that actually does the work

An AI coworker that actually does the work