HomeCatalog🤖 AI / LLMKhoj
Screenshot of Khoj website

// screenshot of khoj.dev ↗

AI / LLM · PRO TIER

Khojpro

Khoj is a personal AI assistant that searches your notes, documents, and the web — answering questions in chat with citations from your own data. Self-hosted, with native clients for Obsidian, Emacs, browser, mobile. Khoj indexes Markdown, PDF, images, org-mode, and chats with the content via any LLM.

🤖 AI / LLM Min 2048 MB RAM Port 42110 (http) Tier pro
// What it is

A closer look.

Khoj is a personal AI assistant that searches your notes, documents, and the web — answering questions in chat with citations from your own data. Self-hosted, with native clients for Obsidian, Emacs, browser, mobile. Khoj indexes Markdown, PDF, images, org-mode, and chats with the content via any LLM.

It's the "personal Perplexity" — your second brain made conversational, on your infrastructure.

// Use cases

What it's for.

Concrete scenarios where teams pick Khoj over the SaaS alternative.

Personal knowledge management

chat with your Obsidian vault, Apple Notes, journal

Document Q&A

ask questions about your PDF library

Research assistant

combine your notes + web search in one query

Daily planning

agent capabilities for calendars, todos, reminders

Multimodal search

find images by text description in your local photo archive

// Who it's for

Built for these teams.

If your team profile matches one of these, Khoj is a strong fit out of the box.

Profile A

Knowledge workers

with growing note libraries (Obsidian, Logseq, Bear)

Profile B

Researchers & students

wanting AI Q&A on their reading list

Profile C

Power users

building a "second brain" with chat-first access

Profile D

Privacy-bound users

who can't push personal notes to ChatGPT

Profile E

Productivity geeks

experimenting with personal AI assistant workflows

// Differentiators

Why teams pick Khoj.

When evaluating self-hosted options for this category, here are the dimensions on which Khoj consistently lands above the alternatives.

  • Native Obsidian / Emacs plugins — chat with notes from inside the editor
  • Multimodal — handles text, images, PDFs in one index
  • Online + offline modes — search local + web in same query
  • Apache 2.0 — fully open, fork freely
  • Agent capabilities — calendar, web search, automation built in
  • Multiple client interfaces — web, mobile, desktop plugins
// Integrations

Connects to.

The stack you'll plug Khoj into — services, protocols, and adjacent apps in the BluixApps catalog.

LLM backends
Ollama (local) or OpenAI / Anthropic / cloud
Note systems
Obsidian vault, org-mode files, Markdown directories
Document formats
PDF, DOCX, plain text, images via OCR
Web search
built-in Google / DuckDuckGo / Bing
Calendar
Google Calendar, iCal sync
Authentication
OAuth (Google, GitHub), magic link
Client plugins
Obsidian, Emacs, web, iOS/Android
// Adoption & deployment

Notable users & community

  • 28k+ GitHub stars
  • Strong Obsidian community adoption
  • Active Discord and GitHub discussions
  • Featured in PKM (personal knowledge management) influencer videos
  • Backed by Khoj AI with sustainable open-core model

What we ship

  • Docker compose: Khoj server + persistent index volume
  • Pinned ghcr.io/khoj-ai/khoj:latest (release-tagged)
  • HTTPS via Let's Encrypt
  • Admin user with random password on first boot
  • Auto-detects Ollama on same VPS for local LLM mode
  • Webhook endpoint for integration with Obsidian plugin
  • Backup hook covers index + database
// Tips & operations

Run it properly.

Operational guidance from running this in production — what to do before you scale, what to lock down, what surprises people.

// PERFORMANCE
Pair with Ollama
for fully offline personal AI — no notes leave your network
// SECURITY
Index incrementally
bulk import of large note libraries takes time; let it run
// OPERATIONS
Set rate limits
public-facing instance can be abused; cap queries per user
// RELIABILITY
Persist /data
index + embeddings live here; mount volume from day one
// DEPLOYMENT
Memory usage
indexing large note libraries needs more RAM than runtime; size accordingly
// SCALING
Update notes via API
Khoj watches filesystem; bulk changes need re-index via API
2048
// min ram (MB)
10
// min disk (GB)
42110
// access port
http
// protocol
pro
// bluixapps tier
pgvector/pgvector:pg15 · ghcr.io/khoj-ai/khoj:latest
// docker image

Project resources

Official sitekhoj.dev ↗
// Alternatives in AI / LLM

Compare with