Most AI tools help you consume content faster. Gistr is where that knowledge actually lives.

I'll be honest about what triggered this.

I was going through my usual workflow - dropping YouTube videos and articles into AI tools, getting summaries, asking a few questions, feeling like I was being productive. Then two weeks later I needed something I had "learned" and it was completely gone.

The summary dissolved the moment I closed the tab.

That's the problem Gistr is built to solve. Not the consuming part, there are a hundred tools for that. The part where knowledge actually stays with you and becomes useful.

What Gistr does

Gistr is a workspace where everything you consume: YouTube videos, PDFs, podcasts, articles, Markdown files comes in, gets processed, and stays organised and accessible over time.

The key distinction from most AI tools: it's persistent. What you add today is still there in three months, fully linked back to its original source. You're not just querying and moving on you're building a library you can actually use.

A few things that matter to us:

Multi-source threads: You can pull a YouTube video, a research paper, and a podcast episode into a single thread and query across all of them simultaneously. Gistr tells you exactly which source each answer came from.

Source grounding: We don't just give you a clean summary and ask you to trust it. Every insight stays traceable to the exact moment in a video or the exact section of a PDF. This matters when you're citing something or making a real decision based on it.

Smart tools built in: Instead of a blank prompt box, Gistr has pre-built tools, smart questions that help you interrogate your material, generate quizzes, create summaries, and take structured notes. It guides you toward understanding, not just output.

PDF precision: Drop in a 300 page document and instead of skimming the whole thing, you pull exactly the section that's relevant to what you're working on. Researchers and students use this a lot.

Who it's for

Gistr makes the most sense if you consume a lot of content as part of how you work or learn and you want that content to actually compound into something useful over time, not just pass through.

Students working across multiple sources. Researchers synthesising papers, videos, and articles simultaneously. Knowledge workers who need to actually use what they read, not just bookmark it.

Where we are

We're early and would love feedback from anyone who deals with heavy research or learning workflows.