Introduction and Key Benefits
Welcome to Frontline Systems’ RASON® modeling language. A cloud service that enables companies to easily embed 'intelligent decisions' in a manual or automated business process, applying business rules powered by advanced analytics."
If you have ever used a modeling language to build an analytic model, you’ll find the RASON language to be simple but powerful and expressive and integrating RASON models into a larger application, especially a web or mobile app, is much easier than with other modeling languages.
Unlike existing "heavyweight" Business Rule Management Systems, with year-long implementation schedules, six-figure budgets and limited analytics power, RASON Decision Services enables creation of decision models powered by a full range of machine learning, optimization and simulation methods, with faster deployment thanks to built-in support for Excel, Power BI, Power Apps, Power Automatic (aka Microsoft Flow) and Dynamics 365 via the Common Data Service, OneDrive and CData's Cloud Hub.
Business analysts and developers can sign up for free trial accounts to evaluate RASON Decision services at http://rason.com which will provide access to tools to compose RASON models, exercise the REST API, try out dozens of example models illustrating use of decision tables, predictive models and machine learning, optimization and simulation, and download the RASON User Guide and Reference Guide in PDF form.
Problems you can solve with the RASON server include linear programming and mixed-integer programming problems, quadratic programming and second-order cone problems, nonlinear and global optimization problems, problems requiring genetic algorithm and tabu search methods – from small to very large (LP/MIP models with millions of variables). You can also solve Monte Carlo simulation / risk analysis problems, and create and solve models with uncertainty, using simulation optimization, robust optimization, and stochastic programming methods. Starting with RASON V2018, all facets of the data mining process are supported, including data exploration and transformation, visualization, feature selection, text mining, time series forecasting, affinity analysis, and unsupervised and supervised learning.