Organize, import + export NotebookLM sources with a click
Most extensions are basic web clippers. Kortex acts as an integration layer, bridging active AI chats with NotebookLM storage. Its standout features include Native LLM Archiving, which adds a one-click import button directly inside ChatGPT, Claude, and Gemini. Unlike others, we focus on data freedom with bulk exports to Markdown, and precision sniping to save specific text blocks rather than whole messy webpages.
Any plans to support custom destinations beyond NotebookLM?
NotebookLM has great features, but it is still lagging in many aspects like letting the users download the chat, particular responses, or even the studio notes. Kortex helps user to export these things easily. Also, you can import your LLM chats directly to notebookLM by clicking only one button. Kortex also offers many features along with these above.
Congrats on the launch! The 'Chat with PDFs' feature is crucial for a second brain app. I’m curious, how are you handling the context retrieval for larger documents? Do you have a way to prevent the AI from hallucinating details not found in the source text? I’m tackling this exact challenge right now with my own tool (SquarePact) for legal contract review, so I'm always interested in how other makers ensure high-fidelity retrieval. Excited to try out the new workflows!
The concept is highly efficient. But what exactly is the core advantage—is it the native LLM archiving feature, or the precision-targeted workflow? How does it maintain consistency during editing? I'm quite curious about that.
I think it's great to add it as a Chrome extension. I love working with my second brain, which in my case is Obsidian, and it would be a huge contribution to the Obsidian community if it could be added as a community plugin within the app. It's fantastic, thanks!
Categories come from the product's launch tags. Most products appear in 2-3 categories. The primary category is listed first.
The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.
Check the similar products section on this page, or browse the category pages linked in the tags above. Each category page shows all products for a given year, sorted by engagement.
A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.