Mathscapes works at the intersection of machine learning, research software, and technical communication. We build models and analysis pipelines for teams working with real-world measurement data, develop the tooling that research and engineering groups need but rarely have time to build, and produce publication-quality technical figures in code. The common thread is legibility — making mathematical work readable to a model, to a reader, and to whoever picks up the code next.