Audience
Data scientists, analytics engineers, and developers who need a unified modeling language and API to build, deploy, and serve advanced optimization, simulation, forecasting, and machine learning decision services in web and mobile applications
About RASON
RASON (RESTful Analytic Solver Object Notation) is a modeling language and analytics platform embedded in JSON and delivered via a REST API that makes it simple to create, test, solve, and deploy decision services powered by advanced analytic models directly into applications. It lets users define optimization, simulation, forecasting, machine learning, and business rules/decision tables using a high-level language that integrates naturally with JavaScript and RESTful workflows, making analytic models easy to embed into web or mobile apps and scale in the cloud. RASON supports a wide range of analytic capabilities, including linear and mixed-integer optimization, convex and nonlinear programming, Monte Carlo simulation with multiple distributions and stochastic programming methods, and predictive models such as regression, clustering, neural networks, and ensembles, plus DMN-compliant decision tables for business logic.