Local & private language models.

Capable AI that runs on your own infrastructure, on your terms.

The position.

Sysqo specialises in local, on-premise, and private deployment of language models, running capable systems inside an organisation's own infrastructure instead of shipping sensitive data to an external API provider.

We hold this position with conviction. Running your own models keeps data private, controls cost, and ends dependency on an outside vendor. It also removes the risk of a model being changed, repriced, or withdrawn from underneath you.

On your infrastructure.

Capable models that run on hardware you own and control.

Your data stays put.

Private by construction. Proprietary data stays inside the building.

No vendor underneath you.

No one can change, price, or withdraw the model you depend on.

What we build.

01On-premise open-weight deployment & fine-tuningStanding up and adapting open-weight models inside your own environment, tuned on your data and owned outright.
02Private RAG over proprietary dataRetrieval over your own documents and systems, where the index and the data never leave the perimeter.
03Quantisation & inference optimisationCompressing and tuning capable models to run on modest hardware: performance without a data-centre's worth of GPUs.
04Sovereignty- & compliance-driven deploymentsArchitectures built for data residency, air-gapped operation, and the regimes that demand them.
05Migration off external APIsMoving a workload from an outside provider onto owned infrastructure, reclaiming control of cost, privacy, and continuity.

Why it connects.

This is the infrastructure the rest of the practice stands on. The most sensitive research we touch, the work toward extending healthy human lifespan, is exactly the data you keep on private, local models. Sovereignty is a precondition here.

A regulated enterprise migrated off external APIs onto owned, air-gapped infrastructure, with capable models running in-house and proprietary data that never left the building.