VaultOS — the governed knowledge layer for enterprise AI | VaultOS
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VaultOS · The knowledge layer

One governed knowledge layer for
people, agents and apps.

Enterprise knowledge sits in a dozen systems, and none of your AI can act on it. VaultOS makes it one governed layer — plain Markdown under an open standard, catalogued in your own Google Cloud, grounding Gemini Enterprise with a citation on every answer, and written back to by people and agents alike. We run the discovery, the build and the handover.

Open Knowledge Format · End-to-end encrypted · Runs in your Google Cloud · Exit with one git clone

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See the stack

In production · not a pitch deck

Open Knowledge Format End-to-end encrypted Runs in your Google Cloud Gemini Enterprise grounded 1,038 documents indexed Zero import failures Cited answers only Scope isolation, fail-closed Exit with one git clone

The stack

Complete infrastructure for knowledge your agents can act on

Three layers. Open formats at the base, your own cloud in the middle, grounded answers on top — and nothing proprietary holding it together.

Markdown with YAML frontmatter under the Open Knowledge Format, in a Git repository you own. Every edit, update and deletion lands as a plain-text diff — auditable, reviewable, revertible. The sync server that keeps every device current only ever holds ciphertext.

  • Just files
  • Plain-text diffs
  • End-to-end encrypted
  • OKF frontmatter

The problem

Your models are ready. Your knowledge isn't.

Every AI programme stalls in the same place — not on model quality, but on the context nobody has made available to it.

Context is rebuilt for every use case

Each new AI project re-solves retrieval, permissions and audit from scratch. The work never accumulates, so the tenth use case costs about as much as the first.

Institutional knowledge leaves with people

Decisions, runbooks and the reasoning behind them live in a few heads and a dozen tools. When someone leaves, the record of why they decided it goes too.

Agents act without checking anything

Autonomous agents execute against policies they cannot see and runbooks they were never given. There is no governed source for them to check before they act.

The VaultOS pipeline visualised: a vault of linked notes connected to Google Cloud's Knowledge Catalog, a grounding index, and Gemini Enterprise. The VaultOS knowledge pipeline, portrait cut.
Under the hood — how we run it

From scattered notes to Gemini Enterprise.

  1. Knowledge, scattered

    Notes, decisions, and runbooks spread across tools and heads. Ours were too — hundreds of notes across six businesses.

  2. One governed vault

    Plain markdown in a linked graph — synced to every device, end-to-end encrypted, mirrored on a schedule.

  3. Catalogued in Google Cloud

    The vault's manifest lands in BigQuery, and Knowledge Catalog registers it automatically — every note governed, discoverable, and readable by agent tools.

  4. Indexed for grounding

    The full vault indexes into a search data store that Gemini Enterprise grounds on. Our last full sync: 1,038 documents, zero failures.

  5. Gemini Enterprise, grounded

    Ask in plain language — every answer cites the exact notes it came from. Scoped views for partners fail closed.

  6. One connected pipeline

    • 1,038 docs indexed · 0 failures
    • Two-way sync, verified round-trip
    • Scoped access, fail-closed
    • Runs on Google Cloud

  7. The loop closes

    documents, grounded. Answers save back into the vault, our agents check policy before they act — and the morning brief cites the graph every day.

  8. Give your AI a memory

    This is the exact pipeline we run internally. Enterprise builds get the same architecture on your own Google Cloud.

    Book the audit call

The real thing

This is our actual production graph — not a diagram.

1,038 notes across six businesses, fully linked, zero orphans after a graph-health audit. Every node is a plain markdown file you own — and every one of them is catalogued in Google Cloud and grounding Gemini Enterprise. This is the vault the assistant answers from.

Meet the assistant
The live VaultOS Obsidian knowledge graph — 1,038 linked notes, zero orphans

One brain, two audiences

The same governed vault serves your people and your agents

Humans ask in plain language. Agents check the same brain before they act. Nobody works from memory anymore.

Your team asks a question the way they'd ask a colleague — "what did we decide about the refund policy in Q1, and why?" — and VaultOS answers from your own history, citing the exact notes. No hunting through drives. No re-deciding what you already settled. Every claim links to its source note, so answers are auditable — not guesses.

VaultOS assistant answering a question with inline citations and a grounded-sources list — product illustration

Try it yourself

Don't take our word for it — ask it yourself

A live scoped assistant over two of our real businesses, DEHN and Snagwise. Sign in with your email for a one-time code, then ask anything — every answer cites its source note, and a question outside its scope simply finds no sources. That's fail-closed isolation, running in production. This one runs on our domain because it's ours; yours runs on yours.

Try the live demo assistant

Built for the enterprise

What holds when this runs on your data

These are the controls running in production today — on our own vault and on client installs.

Runs in your own cloud

Enterprise builds deploy into your Google Cloud project. The vault, the catalog and the search data store stay inside your tenancy, under your billing and your controls.

Encrypted end to end

Sync between devices is end-to-end encrypted, and the sync server only ever holds ciphertext — so the people operating it, us included, cannot read your notes.

Gated and scoped

Assistants sit behind access control with server-side token verification, and retrieval scopes fail closed: a query outside its scope returns no sources rather than a best guess.

Auditable by construction

Every change to the vault is a plain-text diff in Git, and every note is registered in Knowledge Catalog — so “what did we know, and when” is a query rather than an investigation.

We run our own six businesses on it

VaultOS isn't a concept deck. It's the production system behind our own six-business portfolio — catalogued in Google Cloud, grounding Gemini Enterprise. We'll demo the live graph, the sync, and the cited answers on a call.

1,038

documents indexed for Gemini Enterprise grounding

0

import failures on our last full sync

100 %

of answers grounded and cited to the exact note

6

businesses operated on one graph

We didn't build VaultOS to sell it — we built it because we were drowning in our own knowledge. 1,038 documents across six businesses now answer our own questions, with citations, and our agents check the same brain before they act. Then clients started asking how.

Rami Alcheikh
Rami Alcheikh
Founder, Emerge Digital

Engagements

Deployed for you, on your infrastructure

Every engagement is done-for-you: discovery, architecture, import, agent integration and handover. Prices in USD — see full pricing →

Enterprise

OKF Knowledge Graph

For 50–500 person organizations. Discovery, build and agent integration on your own Google Cloud — implementation plus retainer, quoted per engagement.

Team

VaultOS Team

For 5–50 person businesses. From $3,500 setup plus from $270/mo — a shared governed vault and a gated assistant on your own domain, with scoped views that fail closed.

Frequently asked

What is the OKF standard?

Open Knowledge Format is an open, vendor-neutral standard published by Google in 2026. It formalises plain markdown + YAML front-matter in a git repository as the canonical shape for knowledge AI agents can read. No SDK, no proprietary account — any LLM reads the files directly.

Do I need Obsidian?

No. Obsidian is the default editor we configure because its graph view makes navigation intuitive, but your vault is plain markdown files. Any editor that opens text files — VS Code, iA Writer, Typora — works out of the box.

Who stores my data?

You do. Your vault lives on a server you control (a self-hosted CouchDB instance); the sync server only ever holds ciphertext — we cannot read your notes. If you opt into the grounded assistant, your notes are additionally indexed into a dedicated Google Cloud data store for your tenant — scoped, access-gated, and removable — and that choice is yours per tier.

How does the Gemini Enterprise piece actually work?

Two Google Cloud layers, doing different jobs. The vault's manifest lands in BigQuery and Knowledge Catalog registers it — that's governance and discovery, so every note is a catalogued, queryable asset. Separately, the notes index into a search data store that Gemini Enterprise grounds on — that's what makes answers cite the exact notes they came from. Answers can save back into the vault, closing the loop. It's the exact pipeline we run on our own six businesses.

Can different people see different parts of the vault?

Yes — scoped assistant views. Each person or group gets a gated assistant that can only ground on the businesses or areas you allow, enforced server-side and fail-closed: a query outside the scope simply finds no sources. We run a scoped external-partner view in production today.

We have a security review. Are you SOC 2 or ISO 27001 certified?

Not today — we hold neither certification, and we would rather say so than imply otherwise. What we can put in front of a security review is the architecture: enterprise builds run inside your own Google Cloud project under your controls, sync is end-to-end encrypted with the server holding only ciphertext, assistants are access-gated with server-side token verification, retrieval scopes fail closed, and every change to the vault is a plain-text diff in a repository you own. If your process needs a certified processor, the open format means your team can run the same architecture without us.

How long does setup take?

Vault Studio (personal) is live within 3–5 working days of the audit call. VaultOS Team typically takes 1–2 weeks including the knowledge workshop. Enterprise OKF projects are scoped in a discovery engagement — timelines depend on the size of the knowledge base.

Can I cancel anytime?

Yes. The monthly sync and agent subscriptions are cancel-anytime. When you cancel, your vault files stay with you — they're on your server. Nothing is locked inside any Emerge system.

What if I want to switch tools or move away from VaultOS?

Your entire vault exports with a single git clone. The OKF format is readable by any LLM or markdown tool directly — you are not dependent on Emerge or any other vendor to use your own knowledge.

Get started

Give your AI a memory.

A free 30-minute walkthrough of a live VaultOS — the graph, the sync, the assistant that cites three years of decisions. No deck, just the real system — pick a time below.

Calendar not loading? Book directly on Cal.com ↗ or email rami@emergedigital.com.