Simulithic
AI agents predicting experiment outcomes in minutes.
The founders
RN
SS
The company
Simulithic builds AI agents that simulate real user behaviour — hesitating, skimming, abandoning carts — trained on existing session data so product teams can predict the impact of a change before shipping it. The platform returns predictive analytics like lift and confidence intervals within minutes, plugging into session tools such as Clarity and PostHog or its own data capture.
Traditional A/B testing can take weeks to reach significance, and product teams are shipping faster than they can measure. Simulithic bets that agent-based simulation can compress that feedback loop to minutes.
Founded in San Francisco in 2026, the company is part of Y Combinator's Fall 2026 batch and has raised $500K. The founders set out to replace slow, expensive experimentation with pre-release insight drawn from the data teams already collect.
Ryan Ning was a software engineer at Uber and Shopify and did AI research at the University of Toronto; Satyam Singh brings engineering experience from Ramp and YC-backed Bree — a mix of product-scale engineering and applied AI relevant to the problem.
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