Document the AI use
Record the system, provider, data, users, decisions, controls, and review owner.
Regulatory / MAS-regulated firms
MAS-regulated AI is a model risk and governance record, not a feature checklist.
We build private workflows that help regulated firms map AI use, model risk, governance, data, testing, and human oversight into review-ready files. The workflow prepares the record; the firm and its advisers make the regulatory call.
AI inventoryModel riskGovernanceOversight review
Pattern demonstration / same workflow, synthetic material
Fixed-scope setupClient-owned accountsDraft-and-review firstFull handover
Where MAS-related work loses time
The regulator expects the firm to explain its model.
The recurring work is connecting each AI system to its data, model risk, controls, testing, limits, and the people responsible for the outcome.
Prepare the model view
Organize risk assessment, validation, testing, limitations, and mitigation records.
Keep the governance pack
Assemble decision records, monitoring, escalation, and open questions for the owner.
The MAS boundary
The system prepares the record. It does not confirm regulatory approval.
No automatic submission
MAS communications, notifications, and filings remain with the firm and its advisers.
Firm ownership stays firm
Model validation, risk decisions, and senior ownership remain with the regulated firm.
Current guidance only
Current MAS information papers and rules are confirmed against the official text before use.
A first MAS workflow
Start with one AI system and one risk record.
Choose the system
Pick the AI use the firm needs to document, such as underwriting, scoring, triage, or advice support.
Map the record
List the data, users, outputs, controls, model risk, testing, and owner.
Run the evidence check
Compare current records with the defined fields and review missing or stale items.
Build the review pack
Prepare the summary, source index, and open questions for the responsible firm owner.
MAS-regulated AI is easier to explain when the system, risk, and oversight are one 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 get MAS approval?
No. It prepares governance and risk records. MAS approvals and regulatory decisions remain with the firm.
Can it replace model validation?
No. It organizes the evidence. Validation, risk decisions, and oversight remain with the firm and its qualified owners.
How is this different from the FCA page?
That page covers UK FCA-regulated financial services. This page is specific to MAS-regulated firms and model risk governance.
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 AI system
Which AI use should become a risk record?
Tell us the system, the data, the users, and the responsible owner. We will scope the first review pack around the records the firm already holds.