Where files live
The document store stays in your environment, with access rules your team defines and your audit can verify.
Private deployment / self-hosted
AI on your hardware, by your rules.
We design, deploy, and hand over private AI in the environment you control — your cloud, an approved region, or hardware you own. The model and the data path are disclosed, never assumed.
Architecture review from $500Hardware scoped after measurementClient-ownedData paths disclosed
Example only / architecture varies by client
Control is the productRegional optionsClient-owned billingFull handover
Why self-host
Control is the product. The GPU is not the point.
Most businesses do not need their own GPU. They need a data path they understand and can defend.
Where data stays
Choose the region, provider, or hardware that fits your contracts and procurement requirements.
No mystery paths
Any external model or messaging channel is named, configured, and agreed before the system is used.
The three levels
The architecture follows the constraint.
There is no single correct answer. Quality, privacy, residency, and budget decide the path.
Best for most first projects
A private application in your cloud account with a model API on your key. No GPU required.
For location requirements
An approved cloud region or managed service when residency and procurement matter.
For strict control
Model, embeddings, and retrieval on your hardware when external inference is not acceptable.
What it really takes
Measured workloads, not GPU shopping lists.
Hardware is sized after the workload is real. These are starting points, not quotes.
4 to 8 vCPU, 16 to 32 GB RAM
No GPU required for the app and document store. Model usage bills stay on the client account.
From 24 GB VRAM
A starting point for a small quantized text model. Model size, concurrency, and latency decide the real requirement.
Power, cooling, updates, backups
A GPU is one part of the environment. A partner data centre can be more realistic than an office server room.
Not the first promise
We size hardware after the workload is proven. No GPU inventory before a signed scope and deposit.
Straight answers
Common questions.
Does self-hosted mean faster?
Not necessarily. It means the data path is controlled. Quality and speed depend on the model, hardware, and workload.
Do we need a GPU?
No, not for an API-backed pilot. A GPU is only required when the client needs fully local inference.
Is self-hosted more expensive?
Hardware can cost more. The control is the reason to choose it. We compare the paths and their costs before you commit.
Who operates it after handover?
Your team, with a runbook and training. Annual support is available if you want us to stay involved.
Self-hosting is one delivery option. It is not the entire promise. It is the option for clients who need the data path controlled.
Why trust Pristine3D?
We build and operate production software.
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.
We already run live products
Based in Lagos, Nigeria, Pristine3D currently builds and operates smartcards.ng, venu.ng, photoshoot.ng, and ugc.ng in production.
We start with the actual workflow
One input, one output, one test set, and one person who owns the result. We scope a real workflow instead of a transformation programme.
The boundary stays visible
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
Know the starting numbers before you ask.
The final quote follows the workflow. Infrastructure and model bills stay on your accounts.
One Workflow
Starting from$3,500 / ₦2.5m
2 to 3 weeksOne workflow for a small team, with training and handover.
See the one-workflow packageFirm-wide
Starting from$7,500 / ₦8m
4 to 6 weeksMultiple sources, roles, integrations, and admin handover.
See the deploymentAnnual support
Starting from$3,000 / ₦1.5m
per yearStandard 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
The model is not the product. The knowledge base is.
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.
Your corpus, your index
The document store, metadata, and retrieval setup live on accounts you own. No vendor holds the corpus.
Models are swappable parts
Change the model provider, move regions, or go local without rebuilding the knowledge base or the workflow.
The knowledge base is the alpha
Every improvement to the corpus improves the answers, and the improvement stays with you, not with a vendor.
Keep exploring
Related setups.
Start with the constraint
What is your constraint?
Residency, procurement, a no-external-inference rule, or a hardware budget. Describe it and we will map the architecture.