Define the data path
Map which documents, sources, users, providers, regions, and actions the workflow may touch.
IT leadership / deployment, access, and operations
IT managers do not need a second job running an AI product.
We build private AI workflows that fit the IT manager's real constraints: an approved data path, client-owned accounts, named access, simple monitoring, and a runbook the team can operate after handover.
Data pathAccess rolesOperationsHandover
Pattern demonstration / same workflow, synthetic material
Fixed-scope setupClient-owned accountsDraft-and-review firstFull handover
Where IT review time goes
The first question is not the model.
It is where the data goes, who can see it, how it is updated, and who is responsible when something breaks.
Name the controls
Set roles, permissions, administrator access, retention, and the joiner and leaver process.
Plan the ordinary week
Document backups, updates, monitoring, support, and the person who owns the system after launch.
The IT boundary
The system is deployed for the team. It is not a new department.
Client accounts stay client-owned
Infrastructure, model, storage, and integration accounts are set up under the client's control where agreed.
No hidden provider path
Every external provider, region, and retention term is disclosed and approved before material enters.
The runbook fits the team
The operating route is matched to the team's actual support capacity, not an enterprise operations manual.
A first IT-managed workflow
Start with one approved use and one owner.
Choose the use
Pick the workflow a business team needs and the IT constraints it must satisfy.
Map the boundary
List data sources, users, providers, regions, retention, and approved actions.
Run the pilot
Test access, citations, updates, monitoring, and failure behavior with the real team.
Hand over the system
Deliver accounts, training, runbook, support route, and the named operating owner.
A private AI deployment is working when the IT manager can explain the data path and operate the result.
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
Straight answers
Common questions.
Does this add a new system for IT to maintain?
It adds one scoped workflow with a documented runbook. The aim is an operating route the team can sustain, not a platform project.
Who owns the accounts?
Client-owned accounts are the default where agreed. The client controls access, billing, and the credentials after handover.
How is this different from the AI infrastructure page?
That page covers architecture and infrastructure options. This page is the IT manager role: boundary, access, operations, and handover for a first workflow.
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 boundary
Which AI workflow would fit your infrastructure?
Tell us the use, the data path, the users, and the support capacity. We will scope a deployment the team can actually operate.