The proliferation of Large Language Models (LLMs) in recent years has pushed the boundaries of what’s possible in terms of automated code completion and generation. As organisations continue to seek improvements in software development productivity, and as LLMs become increasingly integrated into development ecosystems, understanding their code generation capabilities is essential. In particular, the thesis develops code generation and completion for a Swift-based project, used specifically for iOS application development. The research delves into the creation of an ad hoc model tailored for Swift code generation by fine-tuning existing LLMs. The primary objective is to determine the effectiveness of such models in a corporate environment, thereby providing companies with a clearer perspective on the viability and benefits of adopting such systems.