Deployment

AI deployed on your infrastructure, end to end.

From the first use case to a running system your team actually uses.

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Your infrastructure

Customer records

DB • on-prem

Internal documents

DOCS • private

Support history

LOGS • local

Private AI

on your infrastructure

running

Why on-prem

Running AI on your own hardware or private cloud means your data never leaves your control. Your team can use it on everything, not just the parts that are safe to send to an outside vendor.

Who it's for

You want AI running on your own systems, not a third-party API. You know the use case, or you're close. You need someone to handle everything between that idea and a working system.

What we handle

Hardware planning

Hardware that matches your model, your performance requirements, and your budget, with room to scale.

Model selection

We help you pick the right model for your use case, and let you test-drive options before any hardware is bought.

Setup

We stand up the environment, the runtime, and the serving stack, and connect it to your data.

Tooling

Chatbots, knowledge bases, coding assistants, and the integrations that make it part of how your team works.

Training and tuning

Your team learns to use it. We can stay on to keep it current as models update.

How the engagement works

Scoping call

We talk through your use case, your data, and your constraints.

Model and hardware plan

We recommend a model and the hardware to run it, backed by benchmark data.

Build and deploy

We set up the environment, deploy the model, and connect the tools.

Training and handoff

Your team learns the system, with documentation they keep.

Ongoing tuning

Optional. If you want, we stay on to update models and tune performance over time.

Common questions

Do I need a data center?

No. A single GPU server handles a surprising amount. We size the hardware to your actual load, not a worst case.

How do I know what hardware to buy?

You don't have to guess. That's what our Proof of Concept is for: a short engagement where we benchmark the model on your actual workload and tell you exactly what hardware it needs before you buy anything.

Can we start small?

Yes. We scope something that works now and leaves room to grow.

What happens when a better model comes out?

We swap it in. Staying current is part of the ongoing work.

Ready to deploy AI you control?

Work With Us

AI deployed on your infrastructure, end to end.

What we handle

How the engagement works

Common questions

Related

Ready to deploy AI you control?