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milika/EgoVault

EgoVault

Your personal data, on your machine, under your control.

CI License: MIT Python 3.11+ HF Demo

Every message you sent, every article you saved, every decision you made - scattered across platforms that own your data, monetise your attention, and can delete your history without warning.

EgoVault puts it all back in your hands.


Similar to:

Project What it does Difference
Khoj Self-hostable AI second brain — RAG over personal docs, Obsidian, Notion, web Requires a server; no email/chat import; cloud option available
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Reor Private local AI knowledge management — llama.cpp + RAG over Markdown notes Notes only; no email, Telegram, or social export ingestion
PrivateGPT Chat with local LLM over your own documents — 100% offline Documents only; no platform adapters or multi-source ingestion
Logseq Local-first knowledge base with graph view and AI plugins Manual note-taking; no automated import or enrichment pipeline

EgoVault's focus is automated ingestion from real platforms (Gmail, Telegram, WhatsApp…), enrichment via a local LLM, and hybrid RAG search — all without touching a server you don't own.


Why this exists

Big Tech has had a good run storing your life for you. In return, they read your emails, sell your patterns, and hand your data to whoever asks politely enough. You get a "free" service and a privacy policy nobody reads.

We think that deal is broken.

Your memories do not belong to a corporation. Your conversations are not a product. The decisions, ideas, and relationships you've built over years are yours - and you should be able to search them, learn from them, and take them with you, without asking anyone's permission.

EgoVault is a local-first personal data vault. It runs on your hardware, uses a local LLM that never phones home, stores everything in a single SQLite file you can copy to a USB drive, and answers your questions without sending a single byte to a third party.

No subscriptions. No telemetry. No cloud lock-in.
Cloud sync is a future opt-in - never the default.


Where your data is right now

You probably use some of these every day. Each one knows more about you than most people in your life.

Platform What they hold Users
Gmail Every email you ever sent or received — years of decisions, relationships, receipts, and plans 1.8 billion
WhatsApp Every conversation with friends, family, and colleagues — your real voice, not the public one 2 billion
Telegram Groups, channels, personal chats — often the most candid writing people do 950 million
Instagram DMs, saved posts, your entire visual history — memories tied to a company's servers 2 billion
Facebook / Messenger A decade or more of posts, messages, events, and connections 3 billion

None of them will let you search across all of it. None of them will answer "what did I decide about X three years ago?"
They hold your data. EgoVault gives it back to you — fully local, fully searchable, fully yours.


Hardware requirements

The default model (Gemma 4 E2B, ~3.2 GB) runs on CPU but is significantly faster on a CUDA-capable GPU.


Get started in one line

Windows - PowerShell (Windows 10/11, PowerShell 5+)

irm https://raw.githubusercontent.com/milika/EgoVault/main/scripts/install-win.ps1 | iex

Windows - Command Prompt (runs the same PowerShell script)

powershell -NoProfile -ExecutionPolicy Bypass -Command "irm https://raw.githubusercontent.com/milika/EgoVault/main/scripts/install-win.ps1 | iex"

Linux / WSL - bash or sh

curl -fsSL https://raw.githubusercontent.com/milika/EgoVault/main/scripts/install.sh | sh

macOS - zsh (default) or bash

curl -fsSL https://raw.githubusercontent.com/milika/EgoVault/main/scripts/install.sh | sh

Any platform - pipx (Python 3.11+ required)

pipx install egovault

Then:

egovault chat          # terminal REPL
egovault web           # browser UI - prints a public URL automatically
egovault mcp           # MCP server for AnythingLLM / Claude Desktop

Full installation, configuration, and llama-server setup: docs/installation.md
Can't see the file? View it on GitHub.


What you can do

  • Reclaim your history - import emails, documents, chats, and notes from any platform
  • Ask questions across everything - "What did I decide about X last year?" - one answer, all sources
  • Own the inference - a local LLM reads and enriches your data; nothing leaves your machine
  • Access from anywhere - egovault web punches a secure tunnel so you can reach your vault from any device
  • Take it with you - the entire vault is one file; copy it, back it up, move it freely

Data sources

Source Status
Local files (PDF, DOCX, HTML, Markdown, EPUB, spreadsheets, plain text)
Gmail - Takeout / live API (OAuth2) / IMAP
Telegram export
WhatsApp (via Baileys), Facebook Messenger ⏳ planned
Discord (via Discord.js) ⏳ planned
Instagram, LinkedIn, Twitter/X, TikTok ⏳ planned
Obsidian vault ⏳ planned
Calendar (Google Calendar, CalDAV, ICS) ⏳ planned

Interfaces

Interface How to start
Terminal REPL egovault chat
Browser UI egovault web
Telegram bot egovault telegram

How it works under the hood -> docs/how-it-works.md


Screenshots

Terminal REPL — llama-server auto-starts and chat is ready immediately
Terminal REPL

Browser UI — chat with your vault, tool calls shown inline
Browser UI chat

Remote access login — password-protected page served over a secure WAN tunnel
Remote access login

Telegram bot — full command set accessible from any device
Telegram bot


Roadmap

Adapters coming next

  • WhatsApp, Facebook Messenger, Instagram, LinkedIn, Twitter/X
  • Obsidian vault reader, Calendar ICS

Features coming next

  • Reminders - /remind <text> at <datetime> with due alerts in chat
  • Notes - /note <text> stored and searchable like any vault record
  • Multi-level access control (owner -> guest, passphrase auth)
  • egovault doctor - health-check command

Your data, your rules. Contributions and ideas are welcome - see CONTRIBUTING.md.


Changelog

See CHANGELOG.md for a full history of releases.


License

MIT (c) 2026 Milika Delic

About

Local-first personal data vault — ingest your emails, files & messages, enrich with a local LLM (llama.cpp), and chat with your own data via hybrid RAG (BM25 + vectors + HyDE). No cloud, no tracking, everything in one SQLite file.

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