Choose work worth changing
Start with a task people repeat, a source the business owns, and an output a person can review.
AI rollout / adoption, training, and useful work
AI adoption is not more seats. It is a workflow people keep using.
We help teams choose a small set of useful workflows, set the boundary for company and client data, train the people who use them, and measure whether the work is actually becoming easier. Rollout starts with a business problem, not a license count.
Use cases firstApproved routeStaff trainingMeasure the work
Pattern demonstration / no adoption claim
Why rollout stalls
A company can buy AI and still not change the week.
Adoption usually fails when people cannot see the use case, do not trust the data path, or have no approved way to turn a good prompt into a repeatable workflow.
Give staff a safe path
Separate public, internal, client, and restricted work so people know where a question or file belongs.
Make the new way easier
Train the users, create an owner, capture corrections, and improve the workflow instead of distributing a prompt sheet.
Rollout is a system
Adoption needs ownership at every layer.
Choose the outcome
A sponsor defines the work, boundary, budget, and evidence that would justify continuing.
Test it on real work
Staff need a useful interface, known source, clear limitation, and a way to report what failed.
Keep it maintained
Someone owns sources, permissions, provider changes, training, incidents, and the next improvement.
A grounded rollout
Go from one workflow to a habit.
Inventory actual use
Map current tools, shadow use, repeated tasks, data classes, teams, and the pain people already feel.
Choose a first cohort
Select the users and workflow where the source, output, owner, and success test are clearest.
Train beside the work
Teach the boundary, demonstrate the workflow, collect corrections, and make the useful path faster than the workaround.
Measure and expand
Review usage, acceptance, errors, time, and qualified feedback before adding another workflow or team.
Rollout is successful when a useful workflow becomes ordinary work, not when everyone receives a login.
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
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 run enterprise-wide change programs?
We start with scoped workflows, architecture, training, and operating ownership. Larger change programs can be coordinated when the delivery capacity and scope are clear.
Can you help with an existing ChatGPT or Copilot rollout?
Yes. We can map current use, identify workflow gaps, define data boundaries, and build a private or connected workflow where the existing tool is not enough.
How do we measure adoption?
Measure the defined workflow: use, completion, review acceptance, correction rate, time, errors, and qualified feedback. Do not invent ROI before the baseline exists.
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 rollout problem
Where is AI use already happening without a clear route?
Tell us the teams, tools, workflows, data boundaries, and evidence leadership wants to see.