VaultGuard
Per-file permissions for your AI knowledge-base in Obsidian
What it does
Obsidian is the best thinking and knowledge-base tool ever built for one person. VaultGuard makes it work for a team. It adds encrypted sync, per-file permissions, share-links, AI chat, guest access and audit logs to the vault you already have — no migration, no new app to learn. You write exactly as you do today; VaultGuard protects who can view and work with the files. Point Claude or GPT at the vault and the AI inherits the same permissions your people do. Free if you self-host.
Share your Obsidian vault safely, put any AI on it, and scale it to your whole team. Encryption at rest and in transit, per file permissions, and fast sync. Self host the source available Community edition or use managed VaultGuard Cloud.
Share your vault safely with granular permissions and audit logs, put any AI on it, and scale it to your whole team. Free to self host. Open code you can audit. Nothing to migrate. You built something brilliant in Obsidian. Fast, linked, alive. Then you tried to grow it, and you hit the ceiling. You could build a real one from scratch. Learn retrieval, stand up a database, wire five tools together, spend six months, then train everyone on a system they never asked for. Most teams start, stall, and go back to the wiki nobody opens. So you are stuck between a tool that will not scale and a project that will not end. One living knowledge base that your whole team, and every AI you use, can…from vaultguard.cloud
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- CMCc-md – Zero-cost Obsidian sync across iPhone, Mac, and GitHubFeb 2026 · github.com · ▲8
Here's something I realized: the most AI-native knowledge base isn't a SaaS product with an API. It's a folder of markdown files on your disk. Obsidian stores everything as plain .md files. That means Claude Code (or any AI tool) can grep, read, write, and traverse your entire knowledge base with zero setup. No API keys. No OAuth. No middleware. Just local file I/O. The only missing piece was sync. I wanted my vault on iPhone (iCloud), on Mac (local), and on GitHub (backup + version history) — without paying $4/mo for Obsidian Sync. cc-md is ~400 lines of bash. iCloud handles Apple…


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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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