Name the job
Turn a broad request into an input, output, user group, source, approval step, and definition of done.
AI implementation / from business problem to working system
Turn the AI request into a working pilot.
Pristine3D helps businesses move from a vague AI request to one named workflow, one source, one output, and a testable deployment. We map the architecture, coordinate the right technical pieces, and keep the scope narrow enough to deliver.
Workflow firstArchitecture reviewFixed scopeClient-owned accounts
Pattern demonstration / scope varies
What an implementation partner does
The hard part is making the pieces agree.
A model, connector, interface, and prompt do not become a dependable business system without a workflow, permissions, tests, and an owner.
Choose the path
Compare client cloud, regional, API-backed, self-hosted, retrieval, workflow, interface, and integration choices.
Make it usable
Build, test against real questions, document the limits, train the operator, and leave the agreed system in the client's accounts.
The promise stays narrow
Broad intake. Narrow statement of work.
Private knowledge and workflows
Document search, extraction, drafting, triage, agents, and approved integrations fit the core runbook.
Specialists where needed
Complex cloud, ERP, security, vision, or language work can be scoped and coordinated rather than hidden in a promise.
Say no to unsafe scope
No automatic diagnosis, hiring, credit, tax, legal, or financial decisions without the required qualified controls.
How an implementation starts
A smaller first project teaches more than a transformation slogan.
Describe the painful work
Tell us what people search, write, classify, repeat, or move between systems.
Run an architecture review
Map sources, users, formats, permissions, provider path, region, actions, test questions, and risks.
Deploy a first workflow
Build one interface, one source or connector, read-only or draft-first output, and a fixed acceptance set.
Record what the team owns
Provide the runbook, training, accounts, test record, update process, known limitations, and support boundary in scope.
A good implementation partner makes the AI request smaller, clearer, and more real before making it larger.
Starting points
Buy the result, not an undefined amount of AI.
All infrastructure, provider, storage, and messaging bills remain on client accounts.
One Workflow
Starting from$3,500 / ₦2.5m
2 to 3 weeksOne workflow for a small team, with training and handover.
- One source or connector
- Up to 10 users
- Private chat or approved team channel
- Answers or drafts with sources
- Training and handover
Firm-wide
Starting from$7,500 / ₦8m
4 to 6 weeksMultiple sources, roles, integrations, and admin handover.
- Multiple sources and workflows
- Permissions and admin setup
- Team training and testing
- Runbook and credential handover
- Optional action workflows
Annual support
Starting from$3,000 / ₦1.5m
per yearStandard care for one delivered workflow. Optional. Larger deployments and active monitoring are separately scoped.
- Quarterly health and dependency review
- Bug fixes within delivered scope
- Priority business-hours response
- Documentation and configuration updates
- No new workflows, integrations, or infrastructure bills
Architecture 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
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.
Straight answers
Common questions.
Do you sell a specific model or platform?
No. The workflow and constraint decide whether the setup uses a managed provider, client cloud, regional environment, open tools, or local infrastructure.
Can you handle a large transformation?
The intake can be broad, but delivery starts with a scoped pilot or architecture review. Larger work follows a proven runbook and capacity plan.
What happens if specialist work is needed?
We scope and coordinate it under the client relationship when it fits the project, with access and responsibilities defined rather than assumed.
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 business problem
What has someone asked you to do with AI?
Tell us the workflow, users, source, constraint, and outcome. We will help turn the request into a project that can finish.