Open Notebook: A True Open Source Private Notebook LM Alternative?

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# Introduction

As artificial intelligence becomes a central part of research and learning, the tools we use to organize and analyze information have begun to handle some of our most sensitive data. Cloud-based AI notebooks, while convenient, often lock users into proprietary ecosystems and expose research notes, read-back blogs, and intellectual property to external servers. For students, researchers and independent professionals, this creates a real privacy risk – anything from unpublished work to personal insights can be inadvertently stored, logged or even used to train external models.

The rise of AI-powered note-taking and knowledge management platforms has exacerbated this problem. Tools that integrate summarization, insight extraction, and contextual questioning, but they also increase the amount of sensitive data flowing into cloud services.

Studies show that AI models can unintentionally memorize and reproduce user-supplied data, raising concerns for anyone handling proprietary or personal research. In this article, we explore Open the notebookan open-source platform designed to deliver AI-assisted note-taking while keeping user data private.

# Analyzing the limitations of cloud-only notebook solutions

Cloud-based AI notebooks, e.g Google Notebook LMoffer convenience and seamless integration, but these benefits come with trade-offs. Users are subject to data lock-in, where notes, annotations and context are bound to the provider’s ecosystem. If you want to switch services or run different AI models, you face high cost or technical barriers. Vendor dependency also limits flexibility – you can’t always choose your preferred AI model or modify the system to suit specific workflows.

Another concern is “Data tax“” Every sensitive information you upload to a cloud service is at risk, whether it is from potential infringement, misuse, or undisclosed model training. Independent researchers, small teams, and privacy learners are particularly vulnerable, as they cannot easily absorb the operational or financial costs associated with these risks.

# Description of Open Notebook

OpenNotebook is an open-source, AI-powered platform designed to help users take, organize, and interact with notes while maintaining full control over their data. Unlike cloud-only alternatives, it allows researchers, students and professionals to manage their workflow without exposing sensitive information to third-party servers. At its core, Open Notebook combines AI-assisted summarization, contextual insight, and multimodal content management with a privacy-first design, offering a balance between privacy and control.

The platform targets users who want more than just note storage. It’s ideal for learning blogs with a large readership, independent thinkers looking for a scholarly companion, and professionals who need privacy while leveraging artificial intelligence. By enabling local deployment or self-hosting, Open Notebook ensures that your notes, PDFs, videos and research data remain fully under your control, while still benefiting from AI capabilities.

# Highlighting the core features that set Open Notebook apart

Open Notebook goes beyond traditional note-taking by integrating advanced AI tools directly into research workflows. A focus on self-hosting and data ownership directly addresses concerns about vendor lock-in, privacy exposure, and flexibility limitations suffered by cloud-only solutions. Researchers and professionals can deploy the platform in minutes and integrate it with their preferred AI models or application programming interfaces (APIs), creating a truly customized knowledge environment.

1. AI-powered notes: The platform can summarize large text passages, extract insights, and create context-aware notes that adapt to your research needs. It helps users convert reading material into actionable knowledge instantly.
2. Privacy Controls: Each user has full control over how AI models interact with their content. Local deployment ensures that sensitive data never leaves the device unless expressly permitted.
3. Integration of Multimodal Content: Open Notebook supports PDFs, Youtube Videos, TXT, PPT files, and more, enabling users to consolidate a variety of research materials in one place.
4. Podcast Generator: Notes can be turned into professional podcasts that make it easy to review and share content in audio format with custom sounds and speaker configurations.
5. Intelligent Search and Related Chat: The platform performs full-text and vector searches across all content and enables AI-driven question-and-answer sessions, allowing users to interact with their knowledge base in a natural and efficient way.

Together, these features make Open Notebook not just a note-taking tool, but a versatile research companion that respects privacy without sacrificing AI-powered capabilities.

# Comparing Open Notebook and Notebook LM

Open Notebook as a privacy-first, open-source alternative to Google Notebook LM. While both platforms offer AI-assisted note-taking and contextual insights, the differences in deployment, flexibility and data control are significant. The table below highlights the key differences between the two:

# Deploying Open Notebook

One of the biggest advantages of Open Notebook is its ability to be deployed quickly and easily. Unlike cloud-only alternatives, it runs locally or on your server, giving you full control over your data from day one. The recommended deployment method is Dockerwhich isolates applications, simplifies setup, and ensures consistent behavior across systems.

// Docker deployment steps

Step 1: Create a directory for Open Notebook
This will save all configuration and persistent data.

mkdir open-notebook
cd open-notebook

Step 2: Run the Docker container
Run the following command to start Open Notebook:

docker run -d \
  --name open-notebook \
  -p 8502:8502 -p 5055:5055 \
  -v ./notebook_data:/app/data \
  -v ./surreal_data:/mydata \
  -e OPENAI_API_KEY=your_key \
  lfnovo/open_notebook:v1-latest-single

Description of parameters:

• -d Runs the container in detached mode
• --name open-notebook Container names for easy reference
• -p 8502:8502 -p 5055:5055 Maps ports for web interface and API access
• -v ./notebook_data:/app/data And -v ./surreal_data:/mydata Mount local folders to hold notes and database files. This ensures that your data is protected and persisted on your machine even if the container is restarted.
• -e OPENAI_API_KEY=your_key Allows integration with Open Eye If desired model
• lfnovo/open_notebook:v1-latest-single Specifies the container image

Step 3: Access the platform
After running the container, navigate to:

// Folder structure and persistent storage

After deployment, you will have two main folders in your local directory:

• notebook_data: Stores all your notes, summaries, and AI-processed content
• sorel_data: Contains the core database files for Open Notebook’s internal storage

By placing these folders on your machine, open the notebook backups Data persistence And full control. You can back up, migrate or inspect these files at any time without relying on a third party service.

From creating a directory to accessing the interface, OpenNotebook can be up and running in under two minutes. This simplicity makes it accessible to anyone who wants a completely private, AI-powered notebook without a complicated installation process.

# Exploring practical use cases

Open Notebook is designed to support multiple research and learning workflows, making it a versatile tool for both individuals and teams.

for Individual researchersit provides a centralized platform for managing large read-back blogs. PDFs, lecture notes, and web articles can all be imported, summarized, and organized, allowing researchers to access insights from dozens of sources without manual intervention.

Teams Can use open notebooks as a private, collaborative knowledge base. With a local or server deployment, multiple users can contribute notes, annotate shared resources, and create a collective AI-assisted repository by keeping data internally.

for Eager to learnOpen Notebook offers AI-assisted note-taking without compromising privacy. Context-aware chat and summary features enable learners to engage with content more effectively, turning large volumes of content into digestible insights.

Advanced workflows include: Creating PDFs, web content, and even podcasts As an example of note, a researcher can feed through multiple PDFs, extract key findings, and turn them into a multi-speaker podcast for review or sharing within a study group, while keeping the content completely private.

# Ensuring privacy and ownership of data

Open Notebook’s architecture prioritizes privacy by design. Local deployment means that notes, databases, and AI interactions are stored on a user’s machine or an organization’s server. Users control which AI models interact with their data, whether they use open AI models through the API, native AI models, or any custom integration.

API access allows seamless workflow integration without exposing content to third-party cloud services. This design ensures that context, insights and metadata are never shared externally unless explicitly authorized to do so.

Being fully open source MIT LicenseOpen Notebook encourages transparency and community participation. Developers and researchers can review code, suggest improvements, or customize the platform for specific workflows, reinforcing trust and confidence that the platform is aligned with user privacy expectations.

# wrap up

Open Notebook represents a viable, privacy-first alternative to proprietary solutions like Google Notebook LM. By enabling native deployment, flexible AI integration, and open source contributions, it empowers users to maintain full control over their notes, research, and workflows.

For developers, researchers, and independent learners, Open Notebook is more than a tool. It’s an opportunity to explore new ways to harness AI-AISISTED learning and research, manage knowledge, and actively contribute to a platform built around privacy, transparency, and community.

Shito Olomide is a software engineer and technical writer passionate about leveraging modern technologies to craft compelling narratives, with a keen eye for detail and a knack for simplifying complex concepts. You can also get Shito Twitter.