SIL Global

Built an interactive planning tool for SIL using Python’s geospatial and NLP libraries, LLMs, and integrated datasets from ProgressBible and OpenStreetMap to visualize language access gaps and prioritize translation efforts. By modeling real-world barriers such as travel time and linguistic distance, the tool identified 50+ underserved languages across five key factors. Delivered a dynamic, map-based dashboard using HTML, Python, and Tableau, which was adopted by stakeholders to guide future expansion and global outreach strategies.