01
Data
Context, documents and telemetry remain inside the boundary defined by the organization.
DGL Tech · AI Sovereignty
Your intelligence.
Under your rules.
We build the complete chain required to operate artificial intelligence without surrendering control to third parties: from model to runtime, from hardware to application.
Sovereignty boundary
01 Data
02 Models
03 Runtime
04 Hardware
DGL / CORE NeuroForge
Sovereign applications →
Data, models, runtime and hardware inside one perimeter.
The thesis Sovereignty is not where the cloud is.
Sovereignty is not where the cloud is.
It is who controls the intelligence.
Data residency solves only part of the problem. An organization is sovereign when it can audit, execute, move and evolve its AI without a provider's permission.
02
Models
Weights and specialists are controlled, versioned artifacts evaluated by the organizations that use them.
03
Runtime
Inference runs in a native binary, with no Python or external APIs in the production path.
04
Hardware
The same intelligence can run on CPU, GPU, edge or distributed infrastructure under local control.
The foundation NeuroGrid organizes.
NeuroGrid organizes.
NeuroForge executes.
NeuroGrid
The sovereign infrastructure layer connecting models, compute nodes, policies and applications.
Enter the animated platform →
NeuroForge
The engine that turns models into compact artifacts and runs them locally through a native Go runtime.
See the NeuroForge architecture → Sovereignty applied The infrastructure disappears.
The infrastructure disappears.
The product remains.
Hopus, Claria and Vorbby show the same foundation operating in different contexts — conversation, knowledge and the physical world.
01
Conversational operations
Hopus
AI agents for voice, WhatsApp and web chat, connected to real operating workflows.
In production
02
Academic intelligence
Claria
Voice and text tutoring grounded in institutional content, in advanced pilot.
Advanced pilot
03
Tracking and operational intelligence
Vorbby
A connected-tracking concept intended to integrate device, network, route and operational observability.
In definition
Evidence before promises Every claim has context.
Every claim has context.
Every limit stays visible.
We publish what was measured, on which hardware and at which stage. Research, lab and production are not the same — and this site will not pretend they are.
Examine the evidence →329 tok/s
Ternary decode on H100
Lab benchmark; it does not represent a multi-user production workload.
0
Python dependencies in serving
Support varies by architecture and modality.
The next infrastructure
The first wave gave access to AI.
The next decides who controls it.