AGENARISK uses the latest developments from the field of Bayesian artificial intelligence and probabilistic reasoning to model complex, risky problems and improve how decisions are made. You can use AgenaRisk models to make predictions, perform diagnostics and make decisions by combining data and knowledge about complex causal and other dependencies in the real world. Our clients use AgenaRisk to model a variety of problems involving risk and uncertainty including operational risk, actuarial analysis, intelligence analysis risk, systems safety and reliability, health risk, cyber-security risk and strategic financial planning. AgenaRisk's technology is based on 30 years of research in risk, computer science, AI, Bayesian probability, statistics and smart data. Our technology and accompanying methodology has been published in top academic AI, machine learning, actuarial, decision science and cognitive science journals. AgenaRisk's Bayesian Network technology combines data and domain knowledge, in the form a causal network model of the problem. Bayesian Networks offer numerous advantages over 'big data alone' approaches: It copes with incomplete data and represents real world causal interactions. Bayesian models can carry out prediction and abduction (diagnosis) simultaneously and combine both causal and statistical information.