Old NYC is a Python application that processes historical photographs from the NYPL Digital Collections to create a geolocated, searchable archive. The system ingests metadata, applies OCR to extract text from images, geocodes photos using multiple strategies (title patterns, subject matching, GPT, and a Manhattan grid model), incorporates user feedback corrections, and generates a static website for public access. The architecture follows a modular pipeline design with pluggable geocoders, isolated utility modules, and clear separation of concerns between data processing and presentation. While the project relies on external APIs and contains some legacy shell scripts, it demonstrates active maintenance and thoughtful engineering in handling historical data ambiguities.