The fastest way to search through Medium's vast collection of articles. Discover insights, stories, and knowledge from 190,000+ articles with lightning-fast search powered by advanced algorithms.
Medium hosts millions of articles on every topic imaginable, but finding the right content can be challenging. Spillage cuts through the noise with intelligent search that understands context, relevance, and meaning. We're making Medium's treasure trove of knowledge truly searchable and accessible.
We've built the most comprehensive and fastest Medium article search engine, combining cutting-edge algorithms with real-time expansion capabilities.
Powerful search through 190,000+ Medium articles using BM25 ranking with lemmatization and stopword filtering.
Simply paste any Medium article URL to instantly add it to our searchable database. No waiting, no delays.
Pre-generated indexes and optimized algorithms ensure you get results in milliseconds, not seconds.
Built on the Kaggle Medium Articles dataset with continuous expansion through user contributions.
Every component of Spillage is optimized for speed and accuracy, from the frontend interface to the search algorithms running behind the scenes.
Frontend Framework
Modern React framework providing the sleek, responsive interface you're using right now.
Backend Engine
High-performance Python backend handling search queries and article processing with blazing speed.
Search Ranking
Industry-standard probabilistic ranking function ensuring the most relevant articles surface first.
We started with the Kaggle Medium Articles dataset, providing a solid foundation of 190,000+ articles across diverse topics and authors.
Every article is processed using advanced NLP techniques including lemmatization, stopword removal, and intelligent tokenization for optimal searchability.
Pre-generated inverted indexes and BM25 ranking ensure you get the most relevant results in milliseconds, not seconds.
Dive into 190,000+ Medium articles and discover the content you never knew you needed. Or contribute by adding your favorite articles to expand our database.