Geminos is focused on Causal AI -- fundamentally finding and understanding the why behind AI. Despite huge investments in AI projects, AI is broken. Business leaders need to know about cause and effect if they’re going to make data-driven decisions. Executives ask data teams questions like “what happens if?,” “How does X impact results?,” or “Was it X that caused Y?” Current correlation-based approaches to AI and ML simply can't answer these essential questions. Causal AI is an approach that uncovers the discrete relationships between variables (facets) and a defined business objective (E.g. which variable most strongly impacts customers churn?). By identifying the actions that most directly affect a business objective, Causal AI allows organizations to reduce speculation and risk by making more accurate data-driven decisions.