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Veltrix

architectureHow Intelligence fits together.

A schematic view of the inference layer, model stack, data services, and partner integration points.

whait it isThe technical reality.

GPU-backed inference for open-weight models (Llama, Mistral, Qwen, Falcon and others), fine-tuning pipelines, vector database services, RAG infrastructure, and a metered token-factory consumption model. All in-region, all in-jurisdiction, all multi-tenant by partner.

who it's forBuilt for the partners who deliver it.

System Integrators

Building sovereign AI services for regulated customers.

Operators

Offering AI as a B2B portfolio extension.

Governments

Deploying clinical, legal, or administrative AI on national infrastructure.

what makes it differentWhere Veltrix wins.

Regulator-first architecture

Every inference call has an auditable jurisdiction. Tokens, prompts and embeddings stay where the regulator says they must.

Open-weight, not vendor-locked

We optimize and operate the models customers can audit. No closed black-box dependency on a foreign frontier lab.

Token factory economics

Metered consumption at predictable per-million-token pricing, packaged so SIs and operators can resell with margin.

capabilitiesWhat’s in the box.

Per-tenant fine-tuning
Token-metered billing
Vector database service
RAG infrastructure
Hosted open-weight inference
GPU bare metal for partners
Audit logs for every inference call
Per-jurisdiction inference pinning

how it integratesOne fabric, not five products.