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Private AI for European Organisations

Control your data.
Control your costs.
Then put the intelligence to work.

Local Stack puts private AI on hardware you own. OpenHelm is what runs on it: a working intelligence system with one living model of your business, agents on a shared auditable board, and a human at the helm.

100%
Installed on your machines, your deployment, your database
0
Unclassified records sent to cloud services
1
Licence for one installed system
The Problem

Everyone is told to adopt AI. Nobody explains how to do it without losing control.

01

Chat is not a system

A chatbot answers the question in front of it. It does not run projects, hold state, remember outcomes, or coordinate work. That gap is where value leaks out.

02

Autonomy is not oversight

Fully autonomous agents have produced very public failures. The answer is not less AI. The answer is AI with command structure, gates, and human approvals where it matters.

03

Cloud metering and data egress

Per-seat and per-token pricing scale against you, and every prompt becomes an egress event. For regulated records, client files, and sensitive operations, that is a blocker.

The Foundation – Local Stack

Private AI on hardware you own. That is the ground everything else stands on.

01

Private AI Infrastructure

Open-weight models running on your own machines. Prompts, documents, and outputs stay under your control by default.

02

Sovereignty and compliance

Data residency by construction, not contract wording. Architecture you can walk an auditor through, aligned with EU direction.

03

Cost Architecture

Fixed costs instead of metered surprises. Hardware you own plus a predictable licence, not usage pricing that grows against you.

04

Candid strategy

If private AI is not right for your case, we say so. Substance over hype is the operating model.

What OpenHelm Is

A working intelligence system, not another chat window.

OpenHelm is an installed intelligence system deliberately scaled for real offices. One model of your operation, one board agents must operate through, and traceable facts backed by your own data fabric.

Explore the architecture
  • ✓A frontier brain leads and local GPUs do the volume work
  • ✓A hard data line enforces cloud-ok versus local-only context
  • ✓Every agent operates through one shared board
  • ✓Verification gates close machine-checkable work
  • ✓A data fabric turns records into an auditable business model
  • ✓Outcomes become learning memory that improves month by month
Six Pillars

Six things OpenHelm does that a chatbot never will.

01

Human at the helm

Oversight is architecture, not a checkbox. High-stakes actions gate on human approval.

02

Hybrid, frontier-leading

Frontier judgment where it is earned. Local execution for routine volume at low marginal cost.

03

Hard data line

Cloud-ok or local-only enforced structurally, failing closed, with every crossing logged.

04

System, not chat

Projects and tasks on a board, with visibility, stoppability, and resumable operations.

05

Owned data fabric

Open-source stack, open formats, provenance on facts, and learning memory from outcomes.

06

Bring your own everything

Pluggable providers and portable architecture. No lock-in to any single AI vendor, including us.

In Practice

Three offices, one system.

Professional services office

A small consultancy running many client engagements. Agents draft, reconcile, and prepare while sensitive files remain local-only.

Regulated data operator

A clinic, advisor, or firm where records cannot leave. Local-only processing is enforced by architecture, not policy documents.

Solo operator

One person managing multiple product lines from one queue. Overnight operations progress while judgment calls wait for morning review.

Leadership team

Owners and operators who need AI that is auditable, controllable, and economically predictable before scaling usage.

Next Step

An honest hour on whether this fits your office.

A discovery call covers three things: whether OpenHelm is right for your business, what hardware you would need, and what your data line should look like. If it is not a fit, we will tell you.