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Positioning

Sovereign AI, full control inside your organization

We are not a general AI service provider. We are a specialized team for local and self-hosted AI systems. We make confidential corporate knowledge usable without giving up control over data and infrastructure.

The problem

Valuable knowledge, scattered. The move to the cloud costs control

Corporate knowledge lives in documents, databases, and processes, but it is scattered across file shares, wikis, email, ticketing systems, and specialist applications. It is hard to find and barely usable for automation.

External cloud AI promises fast answers and creates new dependencies on data, models, and infrastructure. For many organizations that is a growing reason to build new AI workloads where the data is allowed to stay in the first place.

CLOUD Act

The jurisdiction counts, not the postcode.

For compliance, data protection, and IT security decision makers, the CLOUD Act is the sharpest argument, and an opener for the conversation. What follows from it is the value of knowledge and automation, not a cloud teardown.

US access reaches everywhere

US providers are subject to the CLOUD Act, regardless of where the data center is located.

C5 does not protect against it

A C5 certification changes nothing about jurisdiction. US sovereign cloud offerings are C5 certified too.

An argument, not a teardown

The argument opens the conversation. What we deliver is sovereign AI, running where your data is allowed to stay.

Out of scope

We do not migrate your cloud. We build your AI sovereign.

Sovereign AI workloads are built new for our clients, where the data is allowed to stay. We do not tear down existing cloud landscapes. That keeps the entry point small, the risk contained, and the benefit concrete.

Our approach

One integrated solution, operable inside your infrastructure

We combine local and self-hosted AI into one system that runs in your environment, not in someone else's cloud.

  • Full-text and semantic search
  • Fuzzy search
  • Knowledge modeling & knowledge graph
  • Named entity recognition
  • RAG with local LLMs
  • Controlled staging
  • Process automation

Principles

What we hold to

Model- and infrastructure-agnostic

The model is replaceable, the implementation is not. Providers can disappear from the market. The architecture must not depend on that.

Hybrid validation

During buildout, a cloud frontier model calibrates quality. In production with sensitive data, the system runs purely locally.

Automated staging

Largely automatic processing with targeted human review where there is uncertainty or criticality, automation first.

Let's scope a bounded use case together

The Sovereign AI Starter is the low-threshold entry point: a short readiness check, then a clearly bounded implementation.

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