Paperclip

What is Paperclip?

Paperclip is a research tool for AI researchers who need to manage information gathered from academic papers. Built with machine learning, computer vision, and natural language processing work in mind, it functions as a memory aid — a second brain for key findings and details from the papers you study.

Its core design principle is local storage: everything you input is indexed and stored on your own computer rather than on external servers. Retrieval requires only a few keywords or phrases in the search bar, the tool works offline, and a one-click reset clears your data whenever you choose.

Who created Paperclip?

Paperclip was developed by Hugo Duprez to give AI researchers a better way to organize and recall information from the papers they read.

What is Paperclip used for?

• Organizing information from AI research papers, ML blog posts, and news articles
• Indexing and storing everything locally on your computer
• Retrieving saved findings through built-in keyword search
• Searching offline without an internet connection
• Keeping data private with local AI processing
• Resetting all data with one click
• Working across platforms, with a browser extension for easier access

Who is Paperclip for?

Paperclip targets machine learning, computer vision, and NLP researchers and specialists, as well as anyone who reads a high volume of papers and needs a private, dependable way to store and recall key findings.

Key takeaways

Paperclip’s main differentiators are privacy and simplicity. Because all data — including AI processing — stays on your machine, research notes are never sent to external servers. Offline support, cross-platform compatibility, and a one-click data reset round out a tool focused on helping researchers keep track of what they read without added overhead.