Know what runs
Record the system, provider, version, users, sources, and business owner.
Governance / AI system audit
An AI audit is an evidence check, not a product inspection.
Audit the system the same way you audit any critical process: what it is connected to, who can use it, what it may output, how outputs are reviewed, and what happens when something fails. We deploy private workflows with that evidence structured for review.
AI inventoryData pathAccess rulesOutput checks
Pattern demonstration / same workflow, synthetic material
Fixed-scope setupClient-owned accountsDraft-and-review firstFull handover
What an AI audit should cover
The questions are normal operational questions.
Most AI reviews fail because the system's owners cannot answer simple questions about its inputs, permissions, outputs, and support route.
Check the boundaries
Confirm access rules, data path, output scope, approvals, and monitoring.
Review the record
Test real outputs, review incidents and feedback, and record fixes and owners.
The audit boundary
The workflow organizes evidence. It does not certify the system.
Current state only
The audit record reflects the system, terms, and configuration at the time of review.
Findings stay expert
Whether an issue is material remains with the business, its auditors, and its advisers.
Remediation stays human
The workflow records open items; the business decides what to change and when.
A first audit workflow
Start with one system and one evidence pack.
Pick the system
Choose one AI tool or workflow with a named owner and current users.
Collect the facts
Record provider, data path, permissions, outputs, training, incidents, and support.
Test the record
Compare the declared state with what users can actually see and do.
Produce the pack
Prepare the summary, source index, open questions, and owners for review.
An auditable AI system is one someone can explain on a normal working day.
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 replace an external auditor?
No. It prepares the evidence an audit needs. The audit conclusion stays with the qualified reviewer.
What makes a good first audit record?
One system with named users, sources, outputs, review checks, incidents, and an owner.
Can it audit public AI tools we already use?
Yes. The inventory can record any tool and compare its current terms and controls with the business's requirements.
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 tool should become an audit record?
Tell us the tool, the users, the data path, and the review owner. We will scope the first evidence pack around what is already true.