Pick the model
Confirm the variant, size, hardware, and quality for the workflow.
Local AI / Ollama
Ollama runs models. It does not run your business workflow.
Ollama is a convenient way to run local models, but a business deployment also needs source-grounded retrieval, access controls, review rules, backup, monitoring, and a support route. We handle the parts that make it usable by a team, not just by a developer.
Model runnerDocument retrievalAccess controlsHandover
Pattern demonstration / same workflow, synthetic material
Fixed-scope setupClient-owned accountsDraft-and-review firstFull handover
What Ollama solves and what it does not
The runner is the easy part.
The hard part is connecting the model to the documents the team trusts, restricting who can see what, and making failures visible.
Add the corpus
Retrieval, citations, metadata, and refresh rules turn the model into an assistant.
Make it supportable
Access, logging, backup, updates, and a named owner are part of the handover.
The Ollama boundary
Local execution is a control, not a compliance claim.
The path is still documented
Sources, model files, hosting, access, and logs are written down.
Local is not automatic quality
The model is tested against the team's real questions and documents.
Someone owns the runtime
Updates, backups, incidents, and model changes need a named owner.
A first Ollama deployment
Start with one document set and one question.
Scope the workflow
Pick the output, users, document set, and latency requirement.
Select the model
Confirm the current variant, licence, hardware, and quality.
Build the assistant
Connect retrieval, permissions, citations, and review rules.
Operate and hand over
Deliver training, a runbook, backups, and the support route.
Ollama can be part of a private AI system. It is not the system by itself.
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.
Do we need Ollama for private AI?
No. Ollama is one model runner among several. We choose the route that fits the workflow and the team.
Can Ollama search our documents?
Ollama runs models. Document retrieval and citations come from the surrounding setup, which we build around the corpus.
Who supports it after handover?
Your team gets a runbook, and annual support can cover monitoring, updates, and normal care.
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 outcome
What should the local assistant do for your team?
Tell us the task, document set, users, and hardware. We will tell you whether an Ollama-based deployment is the right route.