LibreAI / RAG & Knowledge / SurfSense
// rag · MODSetter/SurfSense

SurfSense

Air-gapped, open-source NotebookLM alternative that turns local documents into briefings, decks and podcasts.

★ 16.3k stars⑂ 1.6k forksApache-2.0updated 2026-10
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

SurfSense is an open-source rag & knowledge project by MODSetter (MODSetter/SurfSense on GitHub). It has 16,335 GitHub stars and 1,569 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 7 October 2026.

GitHub stars
16,335
Forks
1,569
License
Apache-2.0
Last updated on GitHub
7 October 2026
Listing
Full install guide
Official site
Official site
// how it works

How it works

  1. Decide if your documents must stay local

    SurfSense fits when files are too sensitive to upload to a hosted notebook tool and you still want cited answers and finished artifacts from them.

  2. Download the desktop installer

    Get the signed installer for Windows, macOS or Linux from the project's releases or download page; no Docker, terminal or account is required.

  3. Pick a model

    Let the app pull a local model for you, or paste a base URL and key for any OpenAI-compatible API; keys are stored encrypted in your OS keychain.

  4. Add documents and open Studio

    Drop in PDFs, Office files or images, ask cited questions, then open Studio to generate a briefing, deck, study guide or podcast from the same sources.

// features

Why people love it

Fully local, air-gapped operation

Parsing, chunking and embedding happen on your computer into a local SQLite index; the app uploads nothing and has no telemetry.

Cited answers over your files

Ask questions across all your documents and every answer cites the source it came from.

Studio artifact generation

Turn sources into summaries, flashcards, quizzes, mind maps, editable .pptx slides, .docx reports, .xlsx spreadsheets, HTML pages and PDFs.

Offline podcasts

Generate a two-host audio conversation from your documents, voiced offline by the bundled Kokoro-82M model.

Any OpenAI-compatible model

Use a local model the app downloads for you, or point SurfSense at any OpenAI-compatible endpoint, including your own local server.

Privacy controls by default

Outbound connections are off by default, with an egress panel listing every destination the app can reach so you choose what to enable.

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// run it

Run it yourself

  1. Clone the repository

    Clone the repo if you want the open-source Docker stack or to work on the code; most users simply download the desktop installer instead.

    git clone https://github.com/MODSetter/SurfSense.git
    cd SurfSense
  2. Download the desktop app

    Install the signed desktop build for your platform from the releases page, which is the supported path in the README.

    # Download SurfSense-Setup.exe / SurfSense-arm64.dmg / SurfSense.AppImage from GitHub Releases - see README for the exact link
  3. Launch and choose a model

    Open the app, let it pull a local model or add an OpenAI-compatible endpoint, then drop in your first documents.

    # Launch SurfSense and follow the in-app model picker - see README for the exact command
// use cases

What you can build

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// faq

Questions, answered

Who maintains SurfSense?

It is an open-source project by MODSetter and community contributors, with a Discord and GitHub Discussions for support and direction.

Is SurfSense free?

The app and its updates are free and the code is Apache-2.0 licensed. The README notes an optional licence that adds plugins and priority support but gates nothing else.

Does it need a paid API key?

No. Every role can run locally: you can let the app download a local model and work with no account or API key, or optionally bring your own OpenAI-compatible key.

How does it compare with Google NotebookLM?

Both produce summaries, flashcards, quizzes, mind maps and audio overviews, but SurfSense runs offline on your machine with your choice of model, while NotebookLM uploads sources to Google and uses Gemini only.

How do I get started?

Download the installer for your platform, pick a model in the app, drop in documents, and ask your first cited question - no terminal or Docker needed.

// keep exploring

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// alternatives

Alternatives in RAG & Knowledge

The most-starred other RAG & Knowledge projects in the LibreAI catalogue — the realistic shortlist if SurfSense is not the right fit.

Get SurfSense

Free and open — grab the source, star the repo, and start creating.