MatrAIx – simulate users before reality (Survey/Chat/Web/App)

MatrAIx lets product teams test tasks with language-model agents conditioned on different synthetic personas. Its README describes sampling persona records, running reproducible tasks across surveys, chatbots, websites and apps, then collecting responses and action histories for comparison.

The public research dataset contains one million filtered personas described through a shared schema. That provides a way to explore how assumed user differences affect a test, rather than repeatedly simulating one generic user. The project explicitly positions this as stress testing and hypothesis generation: variation among synthetic personas does not by itself establish that their responses predict those of real people.