We, at Causal Evidence and Decisions Studio (CEADS), focus on developing machine learning and artificial inference aided causal inference methods for aiding decisions, particularly in high-stakes scenarios. Our tools are flexible, robust and trustworthy, and focus on scenarios where standard causal assumptions are challenged. Our work heavily relies on nonparametric and semiparametric statistics, interpretable ML and generative AI. Our research philosophy relies on first principles thinking and process driven science. Our collaboration partners span across the world -- North America, Europe, Africa and Asia, and work in diverse and high-impact domains from public health and medicine to environmental sciences and ecology, and supply chain management. We aim to make causal reasoning accessible, rigorous, and actionable.