Google NotebookLM Reviews

It can summarize PDFs, Notes, youtube videos, research papers, and lecture materials and convert them into consise short notes. It can explain the contents if asked, generate mind maps, quizes and notes. The best thing is that it supports many file formats. Can generate audio overviewbif one wants to listen. Interface is clean and less distracting. Generates content fast.

It relies on the uploded sources which can be good and bad depending on the richness of the uploaded sources. Its best for large theory based learning.

Earlier I used to struggle with consuming heavy written notes, finding important details took a lot of time and consumed a lot of effort. With this tool I can do that very easily and fast. Sometimes the documents are long and you want to get to the details fast, this is the tool for that.

You can say that you like how NotebookLM turns your team’s documents into a shared, question‑answerable knowledge base that everyone can tap into.

Here’s a clean way to phrase it based on how you’re using it:

I love this platform for being a powerful AI assistant in deciphering the content of the files and creating a very user friendly interface which assist in providing information about the content of the file in a normal human language. It is really useful for understanding documents faster and summarize easily. The capability of this platform really stands out in market research where many documents needs to be gone through in a short period of time. The Audio overview of this platform is really outstanding. Other than this I love the capability of this platform to create mind maps, infographics, video overviews, reports etc. I am totally satisfied with the performance of this platform. The onboarding process was also really easy as it could be done with a google account.

I love almost everything about this platform but I wish that this platform allows note keeping and little bit of editing. I also wish there was a little bit customization possible on the output.

This platform reduces time for going through a documents and providing multiple output that is really useful. All this feature enhances productivity and efficiency of work.

It makes a "podcast" of your notes: it turns your boring documents into a lively, two-person radio show where the hosts explain your material in plain English.

It doesn't make stuff up: Most AI "hallucinates" (lies), but this one is forced to stick to the facts in your specific files. It even shows you exactly which page it got its answer from.

It’s a shortcut for big reading: You can dump in 10 long PDFs and just ask, "What’s the main point here?" instead of reading all 200 pages yourself.

It creates study kits: It can instantly turn your notes into quizzes, flashcards, or a simple study guide to help you prep for a meeting or an exam.

It’s super helpful for everything—slides, quick answers, working papers, videos, and more. I use it for pretty much everything.

I don’t dislike anything about it. It’s been so helpful for everything I need, and it really feels like an assistant.

It helps me give more corporate answers, work faster, and improve my efficiency.

This is really helpful for research, and for creating mock ideas using data maps.

Nothing really. I would segment or prioritize sources so it would be easier to follow. And maybe give them names instead of webpages

Hours of manual research and dozens of open tabs

There are two features that I find very helpful about NotebookLM.

1. The ability to synthesize data from multiple sources

2. The studio features that allows us to create an infographic, slide decks, mindmap and overviews.

In addition, NotebookLM is very easy to use.

Working with Google NotebookLM has fundamentally changed the way I approach research, content synthesis, and knowledge management across multiple projects. From the very first interaction, the tool distinguishes itself from every other AI assistant I have used by enforcing a strict source-grounding paradigm. Rather than pulling answers from the open web or from a generalized training corpus, NotebookLM constrains its responses exclusively to the documents and materials I upload into a given notebook. This architectural decision alone eliminates one of the most persistent frustrations I have experienced with large language models: hallucination. Every claim, summary, or inference the system generates can be traced back to a specific passage in one of my uploaded sources, and inline citations appear automatically so I can verify accuracy in seconds.

The source ingestion pipeline is impressively versatile. I routinely upload a mix of Google Docs, PDFs, Google Slides decks, website URLs, YouTube video links, and even copied plain text. NotebookLM parses each format reliably, extracting the textual content and, in the case of YouTube videos, working from the transcript. I have loaded academic papers, internal strategy documents, lengthy blog posts, and hour-long recorded interviews into a single notebook and then asked cross-source questions that the system answered coherently, pulling evidence from multiple documents at once. The ability to handle heterogeneous source types inside one unified workspace is something I have not found replicated at this level of polish in competing tools.

I have been using Google NotebookLM for about a year, and I find it efficient for tracking and sharing notes with colleagues. Its straightforward setup adds convenience to its efficiency. Google NotebookLM boosts my team’s collaboration and productivity by making it easier to access our collective notes and derive key takeaways. I appreciate the ability to upload relevant files and resources and the AI-driven insights that Google NotebookLM provides, which enhances the velocity of my decision-making and deepens team collaboration.

I dislike how sometimes chat history is lost; it would be beneficial if this was always automatically saved.

I use Google NotebookLM to efficiently track and share notes, extract insights for meetings and discussions, enhance team collaboration, and speed up decision-making and productivity.

I tested it out by pasting a children's story book I wrote and I didn't know what to expect as an outcome. When the processing was finished I was SHOCKED!!!! It was incredible, a conversation of a male and a female character analyzing, commenting, talking about the script is amazing realistic detail. The results was so accurate and the conversation was was flawless that I was super impressed.

The main speaker - the female voice - was the one analyzing the script. The male voice was commenting on the female voice's output. I found the male voice responses a bit repetitive, and a lot of time you would get something like "....Yes you're right, it is indeed great how..." such and such happened. I feel that part needs improvement.

Personally I was just testing it out, BUT if you need to have an audio "commentary" on any script, this tool is simply amazing. It produces amazingly realistic conversations. What it lacks is the creation of Video Content which is what I am after.