Leveraging the same artificial intelligence and machine learning concepts and technologies that power leading business and scientific applications, we are a small Canadian group now forging an innovative way to design interventions and tackle complex policy problems. We believe that better intervention causal models are the key to evidenced-based learning and improved outcomes. We help clients create these models from multiple evidence streams, including deliberative stakeholder narrative, bodies of literature, and available data sets (including open and big data). By integrating these data to tame complexity, we enable our clients to construct powerful visualizations of how their systems work. Our methods and products further support adaptive, long-term institutional learning by providing the means to test intervention models using the right information. It is our view that complex intervention realities, rapid change, and the need to be more accountable, efficient and effective with limited resources, all point to a pressing need to use the best and most innovative tools to solve both new and persistent problems. With the approach we now bring to the community, we feel that organizations no longer have to make a choice between rigor and clarity. Our purpose and mission is to help organizations leverage cutting edge tools to identify the detailed intervention causal structures that drive behavior and change, ultimately supporting more credible strategic design and better outcomes.