Standard ML is a statically typed programming language that is suited for the construction of both small and large programs. Programming in the small is captured by Standard ML’s Core language. Programming in the large is captured by Standard ML’s Modules language that provides constructs for organising related Core language definitions into self-contained modules with descriptive interfaces. While the Core is used to express details of algorithms and data structures, Modules is used to express the overall architecture of a software system. The Modules and Core languages are stratified in the sense that modules may not be manipulated as ordinary values of the Core. This is a limitation, since it means that the architecture of a program cannot be reconfigured according to run-time demands. We propose a novel extension of the language that allows modules to be manipulated as first-class values of the Core language. The extension greatly extends the expressive power of the language and has been shown to be compatible with both Core type inference and a separate extension to higher-order modules.