Venkatram, a sophomore, is building Gigabook LM—an open-source alternative to NotebookLM that runs locally on your own AI model instead of relying on proprietary services

What happened: Venkatram posted on Hacker News seeking collaborators for Gigabook LM, a work-in-progress project hosted on GitHub designed to turn documents into searchable research assets while keeping data private on your own computer rather than uploading to third-party servers.

How it works: Instead of sending documents to a cloud service (like Google's NotebookLM), Gigabook LM lets you run an AI model locally—meaning the AI that processes and indexes your research stays on your machine, not on someone else's servers.

Why it matters: Researchers, students, and professionals working with sensitive documents—grant proposals, medical records, proprietary code—can now build AI-powered research assistants without sharing their files with external companies. This addresses privacy concerns while keeping the cost low since you control the AI model used.