NotebookLM alternatives for source-based research

SurfSense organizes document questions with citations and creates reports, study materials and two-host podcasts from selected sources. Its desktop workflow suits NotebookLM users who want source-grounded work and editable outputs, with local processing or a chosen compatible model endpoint.

Open Notebook suits research organized around source collections, notes and source-based chat. It supports local model backends and configurable audio discussions.

kotaemon suits questions across document collections where checking the source passage matters. Its PDF viewer highlights cited material, with local model and parser options.

RAGFlow combines document extraction with cited answers over complex files and scans. Inspect source chunks or organize the material into wikis, graphs and timelines, with multi-step retrieval for questions that need evidence from several places.

AnythingLLM suits document workspaces with citations and agents. Use its desktop app for personal files or Docker for a shared deployment, choosing local or hosted models.

Surf keeps webpages, videos, documents and notes in a desktop research notebook. Read sources beside your writing and ask questions with citations to PDF pages, video timestamps or webpage sections; small generated applets help explore ideas within the notebook.

Sidekick groups files, folders and websites into research collections for document questions. Its built-in model engine handles conversations, and charts or a canvas let you work with the output. It focuses on research and editing rather than audio overviews.

localGPT suits questions across a document collection when you want to inspect the passages behind an answer. It combines keyword and semantic retrieval and can split complex questions into smaller searches.

Onyx suits research over a shared company document corpus. Workplace connectors supply material, source permissions govern answers and agents can combine internal knowledge with web research to produce reports.

WeKnora turns source documents into a linked wiki and knowledge graph that you can edit and revise. The same knowledge bases support cited questions and agent tasks, making it useful for material that needs ongoing organization as well as answers.

Khoj suits research spread across PDFs, notes and other personal files. Semantic document search and web research feed the same assistant, with custom agents for recurring investigations.

Local Deep Research writes cited reports across private document collections or academic and web sources. Its private-source mode restricts searches to the local library, while autonomous research can refine the evidence it seeks before assembling a report.

Yuxi suits document research with traceable references and shared knowledge graphs. It extracts relationships across sources and lets agents produce downloadable files, with permissions for each team's knowledge bases.

ReadAny grounds book questions in your reading position, selected text and chapter context. Answers can point to source passages, while highlights and Markdown notes keep your research alongside the book.

OpenContracts suits teams comparing legal or research documents through precise annotations. Agents follow citation relationships and propose connections for review, while discussions stay attached to the sources.

AutoRAG Agent searches files and connected archives where they already live, then answers with file, page or line references. It suits research spread across notes, messages and documents. The full agent needs a configured model; Lite provides retrieval without answer generation.

PaperQA2 suits researchers asking questions or looking for contradictions across scientific papers. It ranks supporting passages and writes answers with in-text citations through a command-line or Python workflow, with external services for paper metadata.

Joplin Jarvis brings questions and semantic search to an existing Joplin note collection. Relevant excerpts supply chat context, while its literature-review workflow searches external paper services and writes a report with references.

Inno Agent turns study materials into source-referenced wiki pages and carries learning goals across conversations. Editable learner memory and scheduled review support ongoing study; each instance is designed for one learner.

OpenMAIC turns documents, recordings and other materials into conversational lessons. Generate quizzes or simulations, then revise the course through follow-up requests, with AI teachers and classmates for discussion during the lesson.

Msty’s Knowledge Stacks make document collections available during a conversation. Split chats let you compare what different local or hosted models conclude from the material; podcast generation is not the focus.

Podcastfy covers NotebookLM-style audio discussions drawn from documents, websites or videos. You can adjust the conversation's length, style and voices, or automate generation through its Python package. Speech generation uses separately configured text-to-speech services.