I’ve used enough productivity apps to know most of them eventually hit a ceiling. They’re great for capturing and organizing information, but not so much at understanding it. This is where NotebookLM changes things. It’s a context engine that actually learns from your material and helps connect dots that you miss. Once you start feeding it sources, it transforms them into a format that makes better sense to you.
This is why using NotebookLM side-by-side with other apps can amplify them. Whatever data you capture with an app, NotebookLM can summarize it, pull key points, and also give new insights that the original app may not be able to. I’ve been experimenting with different combinations lately, and here are the apps that I find work better once you pair them with NotebookLM.
Toggl Track
Turning time-tracking data into reflection
Toggl Track has always been one of those apps that make sense in theory. Being able to see where you overspend or underspend your time is actually ideal for someone like me who gets easily distracted. You hit the timer when you start a task, stop when you’re done, and then you have some data. Toggl gives you reports of your time trends, but most of the time, I wouldn’t actually do anything with that information.
Then I started exporting my Toggl data and feeding summaries of my weekly logs to NotebookLM. Instead of static reports, I now actually have a space to ask questions about my time. I can directly ask the AI what categories dominate my mornings, or how often I break flow between creative and admin work – things of that nature. NotebookLM turned that data trail into something closer to a personal audit, and it showed me themes in my workflows that Toggl Track wasn’t able to.
If you’re using Toggl Track or any other time tracking app for that matter, I recommend feeding your logs into NotebookLM. It truly can help you get better insights into where your time goes.
Zotero
Turn it into research powerhouse with NotebookLM
Zotero is the go-to tool for anyone who deals with academic papers, articles, documents, or any research-heavy work. On its own, it’s good for collecting sources and organizing citations. It also keeps your PDF files and saved web pages neatly tagged and searchable. The downside is that that’s all there is to it; it’s mainly a storage tool. You can find what you’ve saved, but it doesn’t really help you make sense of it.
Pairing Zotero with NotebookLM changes that completely. By feeding your Zotero library into a notebook, you can ask the AI to summarize entire collections, pull anything from years-old sources you forgot about, highlight trends across papers, or even compare different authors’ perspectives. It turns your Zotero library from a static reference archive into an interactive research assistant.
Windows Notepad
Minimalism meets intelligence
I love Windows Notepad for how minimalist it is. It’s my go-to tool for writing in plain and Markdown text, and also my first stop when using my plain text stack. This app really is about as basic as it gets. On its own, it’s perfect for jotting down random ideas, as well as fleshing out entire articles or novel drafts. It also has a web link embed function, which comes in handy from time to time. But it doesn’t do much beyond storing these text files.
By feeding my plain text Notepad files into a NotebookLM notebook, my raw and disjointed notes can suddenly become actionable and congruent. The AI can summarize multiple files, extract key points from longer drafts, group related ideas across scattered notes, or even generate new prompts based on my content. What would normally be a pile of scattered text can become a structured and searchable system.
This pairing is ideal for anyone who likes capturing ideas quickly without worrying about formatting, tags, organization, and all that extra stuff. NotebookLM can handle a little disorganized input – which is also why it pairs so well with Google Keep.
Readwise
Turning content highlights into better insights
Readwise already does a pretty good job at helping you collect and revisit what you read. It can sync to a wide variety of accounts, from book apps like Kindle and Apple Books to social media platforms like X, and even websites like Medium. There’s also a browser extension to get articles straight into the app. The purpose is to have a hub of all your reading materials in one place, plus it generates summaries and lets you capture notes on your saved content.
This is all good and well on its own, but I’ve been getting more use out of the app by pairing it with NotebookLM. And the cool thing is that there’s actually a NotebookLM integration for Readwsie. It lets you export your highlights and notes to Google Docs, which you can then search for directly in NotebookLM. From there, you can start asking the AI questions about the key highlights from your saved books and articles. This is a great solution for students, writers, or anyone who deals with a lot of reading materials. Readwise keeps a record and keeps it organized, while NotebookLM synthesizes it.
Unfortunately, Readwise Reader is a paid app. So if you’re looking for a free alternative, I recommend PastReads. It has the same functionality but doesn’t have the NotebookLM integration, so pairing would have to be manual. Once your highlights are in NotebookLM, however, you can prompt the AI the same as I do with Readwise.
Getting apps to do more than store data
Pairing NotebookLM with everyday, somewhat boring, tools can actually make them more useful. Even something as simple as Notepad can end up feeding into a smart system that acts like a sparring partner or interactive assistant. If you don’t use any of these apps in particular, I still recommend pairing up your basic daily apps with NotebookLM to enhance the insights and functionality you get from them. The AI truly can level up anything, from note-taking apps and time trackers to reference managers and read-it-later apps.