PRODUCT CONCEPT · SOVEREIGN AI INFRASTRUCTURE
Your data stays.
The AI comes to you.
Korrion is a concept for sovereign AI infrastructure: the model runs where your knowledge already lives, inside an environment you control, instead of sending raw documents to an external provider for every question.
- Local processing
- Source-grounded answers
- Controlled access
THE PRODUCT IDEA
Not just a box. A controlled AI environment.
The compute node is the entry point. Korrion’s product idea combines models, enterprise knowledge, identities and policies into one environment in which information can be used under control.
DATA AT THE SOURCE
Existing repositories stay authoritative
Original documents remain in the storage your organisation already controls. For retrieval, the node processes released content and holds the required indexes and metadata inside the controlled environment — derived data that must be protected as well.
MODELS AS BUILDING BLOCKS
An exchangeable language model
The language model is a component, not the product. It is intended to be replaceable, so an organisation is not locked into one vendor, one generation of models or one hosting arrangement.
CONTROL AS FOUNDATION
Identities, permissions, traceability
Access rules, policy enforcement, model operation and traceable logging are the long-term substance of the product. Hardware is one possible delivery path, not the thing being sold.
THE PLANNED PRODUCT CORE
An answer is only as good as its basis.
Four steps describe the intended path of a question. The access check comes before the model is handed anything at all.
Ask a question
People ask their question in a familiar interface, in their own words.
Request → permissions → released sources → local model → answer
INTERACTIVE CONCEPT DEMO
See what an answer rests on.
This concept demo shows three intended behaviours: an answer with a traceable source, transparent handling of missing evidence, and retrieval that stays bound to permissions.
QUESTION
Which approval steps apply to a maintenance exception on a high-voltage bay?
ANSWER
According to the released maintenance directive, an exception requires a written risk note, confirmation by the responsible engineer and a second approval by the operations lead before the work window opens.
Answer grounded in two released passages
CONTROL
Your rules.
For your AI too.
Sovereignty does not come from the location of a server alone. What matters is who may retrieve information, which connections are permitted, and what becomes visible outside the environment.
- Question → node
- Node → released passages
- Node → answer
Everything inside the environment
Questions, retrieval, model run and answers stay within the customer environment. No processing path leaves the boundary.
Architecture principle. The concrete implementation and data release are defined for each installation.
Identity before access
Access rules should attach to existing enterprise identities and document permissions rather than a parallel set of accounts.
Connections intentionally permitted
Outbound connections are something an operator decides on, documents and can switch off — not something the system quietly requires.
Traceable processes
Requests, retrieved passages and answers should be reconstructable afterwards, so a decision can be reviewed.
Operation considered
Updates, key handling, monitoring and support paths belong in the architecture from the start, not after the first installation.
POSSIBLE FIELDS OF USE
Internal knowledge. Responsibly usable.
ENTERPRISE KNOWLEDGE
Answers from internal documentation
Procedures, specifications and internal guidance made usable for the people who are allowed to see them, with the source visible next to the answer.
REGULATED ORGANISATIONS
Sensitive material, controlled handling
Organisations working with confidential records keep processing inside their own environment and retain the record of what was retrieved.
CRITICAL INFRASTRUCTURE
Operating knowledge for authorised teams
Operating knowledge and maintenance documentation made accessible to authorised teams. The planned entry point is knowledge assistance — not autonomous control of critical plant.
Possible fields of use. Suitability, integrations and requirements are assessed in each project.
ROADMAP · FEDERATED INTELLIGENCE
Connect intelligence. Preserve data sovereignty.
In the longer view, several local nodes could cooperate without raw data leaving its boundary.
- 01
A released policy package is distributed to the nodes.
- 02
A request reaches a node authorised for it.
- 03
The node processes the request locally.
- 04
Only an explicitly released result is returned.
Vision of a federated architecture. Raw data stays inside local boundaries; shared paths carry policy, request and released result.
DEVELOPMENT PATH
A clear entry. A larger perspective.
- 01
PLANNED ENTRY
Sovereign AI Node
A local, software-defined AI environment bringing together an exchangeable model, document retrieval, identities, permissions and traceable logging.
- 02
PLANNED
Enterprise operation
Updates, monitoring, key handling and support paths for a controlled environment.
- 03
ROADMAP
Data integration
Further released data sources beyond documents, connected under the same access rules.
- 04
ROADMAP
Domain data model
Objects, relationships and rules held in one shared model of meaning.
- 05
ROADMAP
Controlled actions
The AI proposes steps; permissions and required human approvals determine whether anything is executed.
- 06
VISION
Federated collaboration
Local nodes cooperate through explicitly released requests and results.
Ordered development path without delivery dates. Roadmap and vision items are not proven capabilities.
FAQ
Questions before a pilot
No. Hardware is one possible delivery path. The substance is the software for data access, policies, model operation, traceability and controlled collaboration across sites.
No. Existing repositories stay the authoritative source. The node processes released content and holds the indexes and metadata retrieval needs inside the controlled environment.
The intent is local model operation with an exchangeable model, so an organisation is not dependent on one external inference service.
The system is meant to state this openly instead of producing a substitute answer. No invented fallback, no arbitrary confidence score.
No. Local processing can be part of a suitable security and data protection concept. Whether a concrete use meets applicable requirements has to be assessed separately.
The planned entry point is local knowledge assistance with sources and permissions. Broader data integration, a domain data model, controlled AI actions and cross-site federation belong to the further development path.
PILOT
Let’s bring AI to where your knowledge lives.
Tell us which knowledge domain should be first. You can reach our team directly, or prepare a request here and copy it wherever you like.
PREPARE PILOT REQUEST
Korrion pilot request Organisation: — Intended use case: — Contact (optional): —
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