MIMIR — The institutional layer

A living digital twin of your whole company.

MIMIR reads what your company actually does — every decision, message, and transaction — and builds a digital twin: a machine-readable map of how it all works, that intelligence can finally act on.

The shift

Intelligence is commoditizing.

Intelligence per watt is rising exponentially, and as compute and energy keep getting cheaper, the price of raw intelligence approaches zero. It is becoming a commodity, the way electricity did after the first industrial revolution. In 2020, GPT-3 cost $60 per million tokens; today, far more capable models cost cents. When everyone can rent the same reasoning, having it is no longer the edge.

$60$0.10/ 1M tokens

a 100–600× collapse · 2020 → today

The advantage

The edge isn't having intelligence. It's harnessing it.

There is already a vast gap between the intelligence available and the intelligence any company actually uses — the models can do far more than they are ever put to. Closing that gap is the new advantage: not buying intelligence, but harnessing it against your own reality. And that reality is the one thing no one can buy — how your company actually works has never been on the public internet.

The problem

What it says it does. What it actually does.

To harness intelligence, you have to give it your company — what exists, how it connects, what depends on what. But that lives in two records that don't agree: what the company says it does — the documents, the org chart — and what it actually does — the emails, the logs, the decisions made under pressure. The real one is scattered across systems that never share a brain.

EmailCRMLedgerDocsChatTicketsCalendarContracts

Eight systems that never share a brain. You are buried in your own record, and can use almost none of it.

The digital twin

Train on what it did, not what it says it did.

MIMIR builds the twin from the logs, not the documents — a living ontology, a machine-readable map of how your company actually works: who decides, what depends on what, where the real flows run. Where the org chart says one thing and the emails show another, that gap is the insight. One living digital twin. Current, and whole.

How it works

Rules where it can. A model where it can't.

01

Observereads the operational data — emails, transactions, decisions made under pressure. Not the documents.

02

Modelbuilds an ontology: every entity, every relationship, what depends on what.

03

Reasonmost checks are deterministic — exact, auditable rules. A model handles only the hard calls, and can't reason outside your reality.

04

Actacts through permissioned interfaces — and nothing critical happens without a human yes.

What it does

Point it at the work.

The twin doesn't just describe your company — it knows it well enough to act on it. A fleet of agents runs on the twin and does the work itself: closes the books, chases the overdue invoice, drafts the response. Not advice you then have to carry out. Done.

Run experimentsClose the booksShape strategyDraft the board deckChase collectionsForecast cashBrief the team

And before you commit to a decision, you can run it against the model first — change one thing, and see what it does.

Trust

Your data never leaves your building.

Your data

Stays

The raw record never leaves your walls. Not because a contract forbids it — because the architecture makes it impossible. Architectural guarantees, not contractual promises.

Wisdom

Travels

On the MIMIR Network, what your company learns travels between companies as pattern — never as raw data. Your records stay yours. Only the lessons move.

Deployment

It runs on hardware you control.

Sensitive work runs on hardware you control — a box on your desk, a rig on your floor, or GPUs on Danish soil. It's architecture-agnostic: tied to no single model and no single box, so it keeps up as both keep changing. Only safe, pseudonymized work ever reaches the frontier.

On your desk

DGX Spark

A single Grace Blackwell appliance — the whole twin on your desk, and nothing leaves the building.

128 GB unified · fully local

On your floor

RTX PRO 6000 × DGX Spark

A paired local rig: the Spark's unified memory holds the model, the Pro 6000 drives the compute. Real headroom, still entirely yours.

128 GB + 96 GB · fully local

On Danish soil

Sovereign cloud GPU

Datacenter scale, hosted in Denmark — ISO 27001 & ISAE 3402. Never a US hyperscaler.

NVIDIA B200 / B300 · EU-hosted

Local-first · frontier on demand

Whatever the tier, the split is the same: sensitive work stays on your hardware. When a task isn't, MIMIR pseudonymizes it and hands it to the frontier models you already pay for — then rehydrates the answer locally. You get the frontier's intelligence; it never gets your data.

Claude CodeCodexFrontier APIs

Founding partners — a handful, this year

See it on your own company.

We're taking on a handful of founding partners this year — companies that want their operating history working for them before anyone else's does.