# MatrAIx: Simulating Users at Scale Researchers have built MatrAIx, a system for testing AI products and digital services using simulated users instead of recruiting real people. The core problem it solves is real: human testing is expensive, slow, and hard to scale, while traditional benchmarks ignore how different people actually interact with systems. A coding assistant might need to behave one way for a novice who wants hand-holding and another for an expert who wants autonomy. Standard benchmarks just check if code passes tests—they miss these human dimensions entirely. MatrAIx bridges this gap by creating millions of synthetic personas that can interact with products and report feedback from different user perspectives. The system has three main parts. Persona 8B is a database of 8.3 billion persona records built two ways: synthetic personas sampled from a dependency graph that preserves realistic correlations (like how English proficiency relates to primary language), and human-grounded personas extracted from Wikipedia, Amazon reviews, Stack Overflow surveys, and other sources. They're releasing a curated dataset of about 1 million personas—roughly 600,000 human-based and 400,000 synthetic. The MatrAIx Playground lets these personas interact with products across four environments: surveys, AI chatbots, websites, and apps. The third component is a set of 25+ application tasks spanning commerce, software, finance, and healthcare. In validation tests, persona agents powered by Claude and GPT models ran 18,189 trials across eight representative tasks. In a controlled study of 400 trials, personas correctly expressed or suppressed their declared behaviors 91.5% of the time across ten behavioral attributes. The results showed concrete differences—some personas hesitated after price increases, others quit when an AI assistant failed, and tolerance for slow responses varied by user type. The researchers had both human and LLM judges evaluate how well the synthetic personas matched real human behavior. The whole infrastructure is designed to let companies test product changes quickly and catch friction points for specific user groups before deployment, without waiting weeks for human recruitment.