We are big fans NotebookLM here, so much so that it earned our Editor’s Choice award. But it is not the only one An AI tool except where it can aggregate your data to better understand it. In fact, there are many options out there, just none as accessible as NotebookLM.
Maybe you need some kind of output, or you just don’t want Google to handle your data. Not all the following tools have good features like sound either Video overview that helped give NotebookLM its reputation today. Instead, they may offer a more tailored set of skills, whether you’re a reader, analyst or someone who simply prefers more privacy.
Below, we’ll describe a few other AI learning tools that have similar features but may be better suited for you depending on what you’re trying to do, your job or your workflow.
Atlas.org launched in 2024, and its team consists of current students, recent graduates and former faculty. Its purpose is to help you with your homework, and it is organized as such.
When you register for the first time and log in, you will be presented with a series of options, each corresponding to a learning experience. The three main sections are reading, homework and note-taking, and each of those sections has different options to dig deeper.
To study, you can create a study guide, quizzes or flashcards. You can automatically create lecture notes from audio recordings or help find detailed answers to homework questions.
The information you upload to Atlas.org is stored forever, so you’ll have an ever-growing knowledge base about your homework, and you can create dedicated posts for different topics. Like NotebookLM, it also has a mobile app for iOS and Android that lets you study on the go.
Atlas is free to try, but the free tier comes with some steep limitations. You can upgrade to the Pro version for $18 per month.
Yes, it’s another tool with Atlas in its name, but Atlas Workspace is clear about its functions. It mainly focuses on information and semantic mapping and is aimed at scientists and research analysts. It allows you to create a full knowledge base on its servers and map what you want to see when you want to see it. The more sources you upload, the more you’ll get out of it, and since it’s an aggregated database of your sources, you don’t need to remember where you saved a particular piece of information. This is in contrast to NotebookLM’s Notebooks, where sources stand alone as individual projects.
When you upload a source as a PDF, Atlas Workspace will automatically start creating a map of the information, breaking down the main parts of your source — and you can start asking specific questions from there. You can also view the semantic map to get a more visual representation of your sources and how they interacted with the tool.
Atlas won’t be for everyone, and that’s because not everyone needs this kind of tool. To get the most out of it, you’ll need to spend a lot of time working with it, and there’s a significant learning curve to it. However, the Atlas Workspace blog has several in-depth comparisons between its competitors that might be useful for people who are still on the phone.
The free version of Atlas Workspace allows 10 sources and five AI conversations for life, but you will have access to unlimited projects, such as NotebookLM’s Notebooks, but Projects can connect concepts to all projects, with the feature of integrated information. If you choose to get the Pro plan for $20 per month, your source count goes up to 1,000 and you’ll have unlimited AI conversations.
OpenNotebook
Bring us together OpenNotebook deeply in the front, and very close to most of the functionality of the NotebookLM it comes with. However, you’ll need to know what you’re doing to set it up, which can feel incredibly involved if you don’t consider yourself a “technical” person. However, once it’s set up, it can do a lot.
As you would expect, you can upload your sources to OpenNotebook and talk to the AI about it, but what makes this tool special is that you can choose any AI model you want. This will require additional work and, depending on the model, may require a paid API key. You can also use a local LLM if you so choose.
Something that stands out about OpenNotebook is that it is very private. Your data stays with you, and you decide what you share. OpenNotebook is also free and open source.