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Private AI,built on site.

Standaard Tech sends forward-deployed AI engineers into your company. They prepare your data, train the models and install the GPU servers they run on. You own all of it.

Book a scoping call See how it works

Most AI pilots stall before production. The data is messy, security says no to the cloud, and nobody owns the servers. We fix that from inside your building.

Everything happens inside your walls

One process, taken all the way down to the hardware. Each layer ends with something you own.

  1. Process

    We sit with the people who do the work, map one process end to end and agree how we will measure the result.

    You get: a scoped process, a baseline and a success metric you sign off.

  2. Data

    We audit what you have, clean and label it inside your systems, build the pipelines and set who can see what.

    You get: a data set ready for training and retrieval that never left your network.

  3. Models

    We pick open-weight models, add retrieval over your documents, fine-tune where it pays and test against your own cases.

    You get: a model with an evaluation report you can read, rerun and challenge.

  4. Infrastructure

    We size the GPU servers, plan rack space, power and cooling, install the serving stack and wire up monitoring.

    You get: hardware and software you own, behind your firewall, documented.

  5. Operations

    We train your team, write the runbooks and stay close for the first weeks in production.

    You get: a team that runs, updates and extends the system without us.

Engineers on site. Your data stays put.

How Standaard Tech compares with strategy consultancies and AI training courses
Standaard TechStrategy consultancyAI training course
Who does the workOur engineers, on site with your teamConsultants write a planYour staff, after a workshop
Where your data goesNowhere. It stays on your serversUsually to a cloud vendorInto public AI tools
What you have at the endA system in production and a team that runs itA strategy deck and a roadmapCertificates and prompts

Why companies move AI in-house

Your data stays in the building
Contracts, patient files, designs and customer records stay on servers you control.
Costs you can plan
You pay for hardware once instead of per token, so heavy daily use stops growing the bill.
Compliance by design
GDPR, HIPAA and the EU AI Act get simpler when no third party processes your data.
No lock-in
Open-weight models run on standard hardware, and you can swap a model without rebuilding the system.

How an engagement runs

We start with one process and prove the numbers before you commit to hardware.

  1. Scoping call

    We talk through the process, the data and your constraints, and tell you plainly whether AI fits.

  2. On-site discovery

    Our engineers work beside your team, read the data where it lives and agree the success metric.

  3. Build and prove

    We prepare the data, train and test the model, and run a pilot on sized hardware against the baseline.

  4. Handover

    We install the system for good, train your operators and hand over the runbooks.

Questions CTOs ask

What is a forward-deployed engineer?

An engineer who works inside the client’s organisation instead of at a distance. Palantir made the role known; OpenAI and Anthropic now hire for it. At Standaard Tech, forward-deployed engineers learn your process and data on site, then build and run the AI system with your team.

Can a local model match GPT or Claude?

On a narrow task with your own data, an open-weight model with retrieval and fine-tuning often comes close enough, and you control cost, latency and privacy. On open-ended reasoning, frontier APIs still lead. We test both on your cases before you buy hardware and tell you which one wins.

What hardware will we need?

That depends on the model size, the number of users and the response time you need. Many single-process deployments fit on one GPU server; larger rollouts need a small cluster. We size it from load measured during the pilot, and you can buy it from your usual supplier.

How do you handle GDPR and the EU AI Act?

Data and models stay in your environment, so no personal data goes to a third-party AI provider. We document data sources, access rights, model versions and evaluations, which is the record the EU AI Act asks for.

Where do you work?

Wherever your servers are. Our engineers travel to clients in Europe and the United States and work on site for the discovery, the pilot and the installation.

Do you run AI training courses?

Only as part of a handover. We train the people who will operate the system we built together, on that system.

Bring us one process.

In a short scoping call we look at the process, the data and your constraints. You get a straight answer on whether private AI fits and what it would take.

Email hello@standaard.tech