PaperClip

PaperClip is presented as a second brain for AI researchers, aimed at keeping track of daily AI paper reviews. Users can save details from research papers in machine learning, computer vision, and natural language processing, as well as from ML blog posts and news. Saved items can be found again with a simple search. According to the page, saved content stays on the user's machine, the AI runs on-device without sending data to any server or making external API calls, and all saved items are indexed locally. The page states search works offline, and users can reset or delete all saved data in one click. The page shows a counter of 24 bits saved and 0.12MB disk usage. It is built with Svelte and Hugo.

Key features

• Memorize details from AI research papers in machine learning, computer vision, and natural language processing
• Save content from everywhere, including AI research papers, ML blog posts, and news
• Find back saved findings with a simple search
• On-device AI that runs locally without sending data to any server
• No external API calls
• Local indexing of all saved bits
• Offline search support without internet connection
• One-click reset of saved bits and deletion of all data

Best suited for

• AI researchers reviewing papers daily
• Machine learning, computer vision, and NLP practitioners tracking research findings
• Users who want to keep research notes private and local

Pricing

Not stated on the website