Built for GDPR review
The Data Protection Ombudsman supervises GDPR compliance in Finland. The deployment ships with documented purposes, processors, and access rules that a review can actually use.
Self-hosted AI / Finland
Private AI deployed for Finnish businesses with hosting in a Nordic region such as Stockholm, a disclosed model path, and a design built for the Data Protection Ombudsman's GDPR review culture, where impact assessments are part of the normal process.
Example only / architecture varies by client
Why it matters here
Impact assessments and documented processing are the expected way to build, and the deployment matches that culture.
The Data Protection Ombudsman supervises GDPR compliance in Finland. The deployment ships with documented purposes, processors, and access rules that a review can actually use.
A Nordic region such as eu-north-1 (Stockholm) is the default, with fully local deployment for stricter requirements.
The data path and risk material are documented in a form that supports a data protection impact assessment where one is required.
The three levels
There is no single correct answer. Quality, privacy, residency, and budget decide the path.
App and document store in your account in eu-north-1 (Stockholm), with the model on your key. No GPU required.
An approved cloud region or managed service when residency and procurement matter.
Model, embeddings, and retrieval on your hardware when external inference is not acceptable.
What it really takes
Hardware is sized after the workload is real. These are starting points, not quotes.
No GPU required for the app and document store. Model usage bills stay on the client account.
A starting point for a small quantized text model. Model size, concurrency, and latency decide the real requirement.
A GPU is one part of the environment. A partner data centre can be more realistic than an office server room.
We size hardware after the workload is proven. No GPU inventory before a signed scope and deposit.
Straight answers
A Nordic region such as eu-north-1 (Stockholm), or on-prem when the requirement is stricter. The region is documented in the architecture.
No. Supervision applies to processing under the GDPR, and where an impact assessment is needed, the deployment provides the documented data path and risk material for it.
The material that a DPIA needs — data flows, purposes, processors, access — is part of the handover. Whether a full assessment is legally required depends on the processing.
Yes, from €3,300 for a first workflow, with USD and naira floors unchanged.
Why trust Pristine3D?
Pristine3D Ltd builds and operates live digital products, and we run private AI workflows internally as part of our own operations. We scope around your real workflow: the documents you own, the questions your team asks, and the access boundary you approve. Based in Lagos, Nigeria, we work remotely with clients worldwide.
Based in Lagos, Nigeria, Pristine3D currently builds and operates smartcards.ng, venu.ng, photoshoot.ng, and ugc.ng in production.
One input, one output, one test set, and one person who owns the result. We scope a real workflow instead of a transformation programme.
Cloud, model, storage, and messaging accounts stay in your name. The chosen data path, access rules, test record, documentation, and training are part of the agreed scope.
Pricing / fixed scope
The final quote follows the workflow. Infrastructure and model bills stay on your accounts.
One workflow for a small team, with training and handover.
See the one-workflow packageMultiple sources, roles, integrations, and admin handover.
See the deploymentStandard care for one delivered workflow. Optional. Larger deployments and active monitoring are separately scoped.
See supportArchitecture review from $500. Standard annual support is $3,000 / ₦1.5m per year for one delivered workflow. New workflows, integrations, active monitoring, and infrastructure are separately scoped; infrastructure, model, storage, and messaging bills stay on client accounts. Full pricing and what changes the quote
Own your knowledge base
Documents, the retrieval index, access rules, and the workflows built around them are the asset, and they compound. We deploy so the knowledge base stays yours: on your accounts, in the environment you choose, under access rules your team defines. The model behind the answers is a connector, so the knowledge base moves with you, not with a vendor.
The document store, metadata, and retrieval setup live on accounts you own. No vendor holds the corpus.
Change the model provider, move regions, or go local without rebuilding the knowledge base or the workflow.
Every improvement to the corpus improves the answers, and the improvement stays with you, not with a vendor.
Keep exploring
Start with the constraint
Residency, procurement, or a no-external-inference rule. Describe it in English or Finnish and we will map the architecture.