This document describes WebCat, an app that automatically classifies websites into predefined categories using Apache Spark. It trains a Naive Bayes classifier on over 2,500 previously categorized websites and their crawled text features. New websites are categorized by extracting their text features and having the model make predictions. The high-level architecture includes link collection and crawling services that scale independently, with the classified data stored in a database and trained on Spark. Suggested improvements include allowing users to provide feedback to update the model, upload their own training data, define custom categories, and implement a public API.