Khoj: What It Is, Key Features, and How to Get Started

What it is

Khoj is an open-source personal artificial intelligence application designed to act as an interactive “second brain.” In personal knowledge management, a second brain refers to a centralized digital archive where individuals store notes, documents, references, and ideas so they can retrieve and synthesize that knowledge whenever needed. Khoj serves as an assistive bridge over this information, enabling individuals to search, query, and reason across their accumulated archives through natural conversation.

The application is released under the GNU Affero General Public License (AGPL-3.0) and maintains a commitment to remaining open source and self-hostable. Architecturally, Khoj is designed to scale flexibly. It can operate on individual consumer hardware as a private, on-device assistant or expand into a cloud-scale deployment suitable for enterprise environments.

Rather than locking users into a single model vendor or storage ecosystem, Khoj connects to a wide variety of machine learning models. It supports both local, offline language models and cloud-hosted commercial artificial intelligence services. This architecture allows individuals to retain full sovereignty over their private notes and files or take advantage of hosted cloud infrastructure depending on their privacy and convenience requirements.

What it can do

Khoj brings together a broad set of retrieval, synthesis, and automation capabilities designed to streamline daily work:

• Multi-Format Document Ingestion: The platform can parse and reference many everyday file types. These include PDFs, plain text files, Markdown documents, Microsoft Word files, Org-mode files, Notion pages, and image files. When relevant, Khoj references these shared materials to ground its answers in your personal data.
• Semantic Search and Retrieval: Rather than relying exclusively on exact keyword matching, Khoj incorporates advanced semantic search. Semantic search analyzes the conceptual meaning of words in a query, which allows people to locate relevant notes and documents quickly using everyday natural language even if the exact search terms are not present in the text.
• Hybrid Answering from Docs and the Web: In addition to retrieving facts from uploaded private files, Khoj can access the public internet. This allows it to combine private context with real-time public information to provide comprehensive responses.
• Broad Model Support: Khoj can connect to both local and cloud-based Large Language Models (LLMs). The project README lists compatibility with models such as GPT, Claude, Gemini, Llama (including Llama 3), Qwen, Gemma, Mistral, and DeepSeek. This flexibility lets users select models that align with their local hardware capabilities or cloud preferences.
• Custom Autonomous Agents: Users can design specialized agents configured with unique personas, tailored knowledge bases, designated chat models, and specific tools to handle distinct tasks or organizational roles.
• Research Automation and Newsletters: The system can automate repetitive research routines. It can deliver smart notifications and custom research newsletters directly to a user’s email inbox on a regular schedule.
• Multimodal Voice and Image Features: Beyond standard text interactions, Khoj allows users to talk out loud, play back responses as audio messages, and generate images directly within the conversation.
• Multi-Platform Access: Khoj is accessible across a wide selection of platforms. Users can interact with it through modern web browsers, dedicated desktop software, mobile phones, WhatsApp, and text editors or note-taking systems like Obsidian and Emacs.
• Companion Projects and Benchmarks: According to the project README, the team has introduced Pipali, an open-source AI coworker designed to operate on a user’s computer. Additionally, the project README notes that readers can review details regarding Khoj’s performance on modern retrieval and reasoning benchmarks on the project’s official blog.

How to get started

Getting started with Khoj can follow two primary paths depending on whether you prefer instant access or complete local control:

1. Using Khoj Cloud: For users who prefer to skip manual server administration, Khoj provides a hosted version accessible via any standard web browser at app.khoj.dev. This option provides immediate access to the assistant with no installation or system configuration required.
2. Self-Hosting Locally: Users who prioritize data ownership and privacy can host Khoj directly on their own computer. The project documentation highlights that Khoj is capable of running on standard consumer hardware. Detailed installation and setup instructions for self-hosting are maintained in the official documentation.
3. Connecting Client Applications: Once an instance is running—either on the cloud or locally—users can choose their preferred way to interact. You can log in through the web interface, install the desktop application, access the assistant from your phone, connect it through WhatsApp, or configure plugins for note-taking platforms like Obsidian and Emacs.
4. Supplying Knowledge: To build your personal assistant, share your notes and reference files with the application. Adding documents such as Markdown notes, Word documents, PDFs, Org-mode archives, or Notion exports enables the assistant to index the content for semantic lookup and conversational Q&A.
5. Setting Up Agents and Workflows: After connecting your materials, you can configure custom agents, designate which local or online models should process your queries, or schedule automated research summaries to arrive in your email inbox.

Pricing and requirements

Khoj is open-source software distributed under the AGPL-3.0 license. Because hosting choices, cloud features, and managed options can vary, all pricing and plan details are subject to the official page at khoj.dev.

For organizations needing team-oriented capabilities, Khoj Enterprise provides multiple deployment models. According to the project documentation and website, enterprise options include a managed cloud service, an on-premises setup, or a hybrid configuration. Further information regarding team deployments can be reviewed at khoj.dev/teams.

In terms of technical requirements:

• Hosting Hardware: The documentation states that self-hosted setups can run on standard consumer hardware for personal privacy.
• Supported Client Environments: Users can access the platform using web browsers, desktop operating systems, mobile devices, WhatsApp, Obsidian, or Emacs.
• Model Compatibility: Users require either an internet connection and API credentials to access online models (such as GPT, Claude, Gemini, or DeepSeek) or an environment capable of running supported local models (such as Llama, Qwen, Gemma, or Mistral).

Who it is for

Khoj is suited for a variety of users who want a structured, AI-assisted approach to managing information:

• Note-Takers and Knowledge Workers: People who maintain extensive collections of notes in Markdown, Org-mode, Notion, Word, or PDF format and want an intelligent assistant to locate, connect, and synthesize concepts across their records.
• Obsidian and Emacs Users: Enthusiasts of text-first productivity tools who value having an AI assistant deeply integrated into their existing editing and note-taking environments.
• Privacy-Conscious Individuals and Developers: Users who prefer to keep their documents and personal thoughts on their own machines, leveraging open-source software and local LLMs to avoid sending personal files to third-party cloud servers.
• Researchers and Content Creators: People who conduct recurring research and can benefit from scheduled email newsletters, automated web browsing, and multi-source document queries.
• Teams and Organizations: Groups looking for adaptable deployment options—ranging from cloud to on-premises installations—to supply an organizational knowledge assistant across diverse tools.
• Open-Source Supporters: According to the project README, Khoj is sustained by an active community and is used by thousands to boost productivity.

Alternatives

AnythingLLM is an alternative application in the personal AI and document interaction space.

NotebookLM is another tool designed for working with notes and information using artificial intelligence.

Sources

• Khoj GitHub Repository
• Khoj Documentation
• AnythingLLM
• NotebookLM