Humata
ProductivitySearch, summarize and compare uploaded documents with source-linked answers. Humata adds team-oriented document access and page-based plans for ongoing knowledge work.
Questions across filesCited passages
YOUR RESEARCH WORKSPACE / SOURCES, NOTES AND QUESTIONS
Open Notebook
A free self-hosted research workspace for collecting sources, asking questions, writing notes and creating audio summaries with separately configured AI providers.
Official Open Notebook screenshot showing sources, notes and notebook chat; illustrative project materialExplore the image ↓
What you can do with it
What this tool is for
Open Notebook is a research workspace that brings sources, notes and model-assisted conversations together. The project describes multiple notebooks, search, content transformations and podcast generation, while allowing the operator to choose supported AI providers. It is independently developed and should not be confused with Google NotebookLM.
The useful distinction is control over the research environment. You can decide where the application runs, what material enters a notebook and which model handles a task. That does not automatically make every workflow offline: extraction, embeddings, chat and speech may each use a different configured service.
01
Prepare an article research file
02
Build a personal study notebook
03
Compare document versions
04
Make an audio review draft
A closer look at the product
Official product image. Click to inspect the details.
Product interface and examples
Key features, practical tasks
Capabilities in practice
- Notebook organization: Group material around a question or project rather than placing everything in one conversation. Use meaningful source titles and notes so the purpose of a collection remains understandable later.
- Several input formats: The source guide documents files, pasted text and web links, plus supported media processing. Extraction depends on the format and enabled components; inspect the resulting text before asking detailed questions.
- Explicit context selection: The chat guide distinguishes full-source, summary and excluded context choices. Decide which material is relevant to the current question instead of assuming that every imported source should be sent to the model.
- Model choice: Documented provider configuration includes local options such as Ollama and compatible endpoints. Configure the language and embedding roles deliberately, since one working model connection does not establish every feature.
- Search and reusable notes: Search can help locate relevant material, while notes preserve human observations or model-assisted drafts. Keep an editorial distinction between original source content and generated interpretation.
- Content transformations: Reusable processing instructions can turn sources into summaries or structured extracts. Define the desired fields and check missing information instead of allowing the model to fill every section by guesswork.
- Podcast generation: The project documents episode and speaker configuration for audio dialogue. Review the underlying script and the selected speech provider before treating generated audio as a finished explanation.
Get started, step by step
- 01
Choose the deployment and models
- 02
Add a small source set
- 03
Ask a bounded question
- 04
Save a reviewed result
A practical first workflow
A practical first workflow
- Choose the deployment and models. Follow the current local or hosted setup guide. Configure the storage and provider roles required by the intended task before importing a large collection.
- Add a small source set. Start with a few permitted files or links and inspect extraction. A source listed in the interface may still need processing or a configuration adjustment.
- Ask a bounded question. Select relevant context and request references where supported. Compare the response with the original material and preserve uncertainty when the source does not answer.
- Save a reviewed result. Convert useful findings into notes with source links. Keep model and processing settings recorded if you need to reproduce a result or generate audio from it later.
Example prompt or task: Using only the selected sources, compare their explanations of this topic. Separate shared findings, disagreements and missing evidence, and provide source references that I can check before saving the note.
This is an editorial workflow example. References are aids to verification, not a guarantee that a generated statement is supported.
Find the right plan for you
Free open-source software
Explore official plans ↗Free software Inference and speech services are separate
A documented local-model route avoids a required cloud-model subscription. Each enabled processing stage still needs appropriate resources and configuration.
What is free and what can cost extra
Open Notebook is MIT-licensed software that can be self-hosted without purchasing an application subscription. The official local setup describes a route using local language and embedding models, with the user supplying the hardware and storage.
Cloud language models, embedding APIs, transcription and text-to-speech services may each add costs. Podcast support in the application does not include unlimited paid voice generation. Check the provider combination for the exact workflow rather than assuming the whole notebook is free because the interface is open-source.
A few things worth knowing
Frequently asked questions
Is Open Notebook free?
The MIT application is free to self-host. Models, hosting and speech resources are separate.
Is it Google NotebookLM?
No. It is an independent open-source project.
Can I use local models?
The official documentation includes a local-model route. Configure both language and embedding needs.
Does importing a file prove it was read correctly?
No. Check extraction and processing status.
Can I choose the context for a question?
The chat workflow provides source-context choices.
Are podcasts automatically free?
No. The selected generation and speech providers determine the resource cost.
Are citations always correct?
No. Check the referenced source passage before relying on a claim.
The details behind your decision
Explore platforms, inputs and outputs, licensing, and access requirements.
Four useful starting projects
Four useful starting projects
- Prepare an article research file: Collect permitted primary sources and ask focused comparison questions. Save a note separating confirmed facts, disagreements and points that need another source.
- Build a personal study notebook: Add a small set of course materials and create revision questions. Check answers against the relevant passage rather than judging them only by how confidently they are written.
- Compare document versions: Keep the versions clearly labeled and ask about one defined change. Verify the passages directly before reporting that a requirement or conclusion has changed.
- Make an audio review draft: Turn reviewed notes into a short audio discussion for your own review. Listen for invented transitions or oversimplification, then correct the script before sharing.
Platforms, inputs, outputs and setup
Platforms, inputs, outputs and setup
The project documents container-based and developer installation routes. It uses persistent application and database storage, so backups and a clear update process matter when notebooks become important working records.
Scanned documents and image OCR require the appropriate processing engine, while audio and video need suitable transcription configuration. Web extraction can fail or return incomplete text. A small import review is often more useful than immediately adding hundreds of files.
Data, permissions and licensing
Data, permissions and licensing
Self-hosting controls the application location, but configured cloud providers may receive selected text or audio. Map the extraction, embedding, chat and speech stages before importing sensitive material.
Configure credentials, encryption settings and access controls according to the deployment guide. Preserve source rights and avoid exposing a personal research instance publicly with development settings or shared secrets.
Sources, documentation and help
Official sources and review date
Official sources and review date
Reviewed October 3, 2026. Product facts come from the official sources below. Suggested projects, prompts and review methods are FindGoodAI editorial guidance, not measured performance results.
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