AI & Analytics

Analytics applications

With the increasing availability of connected and big data, automated regressions, forecasting, predictive machine learning & AI helps modern organizations to reach their business, policy and scientific goals, or help data journalists to reveal hidden patterns. Our applications can run tens of thousands of model variants and help to focus data analysis human intuition and knowledge on the most promising leads. The use of these analytics methods relies on often hundreds of standardized and independent variables (“features”), which cannot be consistently maintained by error-prone human analyst work. Our data integration applications makes sure that the data is available in a statistically tidy, easy to use format. Our analytics applications adhere to the tidy modelling standards, which allow the proper documentation and comparison of hundreds of model families from the simpler linear and multiple regressions to advanced non-linear models, supervised and unsupervised models.

Organization investing into reproducible research can rely on tens of thousands of analytical model candidates for their work — putting traditional analysts into an impossible competition. We believe that our applications should produce thousands of model candidates and comparisons, and leave human wisdom and intuition to refining the most promising leads.