In its original formulation, in conjunction with the modeling engine, Syberia serves as a machine learning classifier development framework.
The modeling engine provides an opinionated unified framework for fast iteration on classifier development and deployment. It is founded on convention over configuration and aims to solve the problems of classifier-specific data preparation and classifier-specific modeling parameters.
The more general vision for Syberia is still in progress, but aims to unify the currently disparate realms of R packages, script codebases, Shiny dashboards, R web apps, and reproducible analysis. In the viewpoint of the author, R is syntactic sugar around LISP, which enables arbitrary computation; Syberia is an attempt to support this conjecture by allowing the construction of arbitrary software projects within the R programming language, thereby finally outgrowing its long-overdue misconception as a statistical tool.