Map the estate
Record each AI tool, provider, users, data, output, and owner.
Governance / regulated industries
Regulated AI is an evidence problem, not a policy-writing exercise.
We build private workflows that help regulated teams keep the AI governance record: inventory, data path, risk assessment, controls, review, incidents, and improvement in one reviewable file. The firm and its advisers make the regulatory call.
AI inventoryRisk recordControl checksEvidence pack
Pattern demonstration / same workflow, synthetic material
Fixed-scope setupClient-owned accountsDraft-and-review firstFull handover
Where regulated AI governance gets stuck
The evidence is spread across tools and folders.
A reviewer should be able to ask who owns the system, what it may do, how it is controlled, and what happened when it failed.
Connect the controls
Link risk assessment, testing, limitations, approvals, and monitoring.
Keep the learning loop
Log errors, reviews, fixes, and the owner of each follow-up.
The governance boundary
The system organizes proof. It does not confirm regulatory approval.
No automatic contact
Regulator communications and notifications remain with the firm and its advisers.
Risk decisions stay expert
Materiality, sufficiency, and remediation remain professional judgments.
Current rules only
The relevant rules and guidance are confirmed against the current official text.
A first governance workflow
Start with one system and one review pack.
Choose the system
Pick the AI use the business needs to govern first.
Map the record
List the data, users, outputs, controls, testing, and owner.
Run the evidence check
Compare current records with the defined fields and review gaps.
Build the review pack
Prepare the summary, source index, and open questions for the owner.
Regulated AI governance is more credible when every system has a date, an owner, and a record.
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 make us compliant?
No. It prepares the governance record. Compliance remains with the firm and its advisers.
Which industries is this for?
Financial services, legal, healthcare, insurance, and other regulated teams that need a reviewable AI inventory.
Can it replace a risk team?
No. It organizes the evidence. Risk judgment stays with the qualified owners.
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 system
Which AI use should become a governance record?
Tell us the system, the data, the controls, and the responsible owner. We will scope the first record around them.