Record the current process
Measure time, handoffs, errors, backlog, rework, unanswered questions, or other evidence before the workflow changes.
AI measurement / prove the workflow before expanding
Measure the workflow before you claim the ROI.
We help define what a first AI workflow should improve and how the team will know. That means a baseline, a fixed test set, an accepted output, a review path, and evidence of time, quality, risk, or capacity change after the system is used.
Baseline firstAcceptance criteriaCorrection rateNo invented ROI
Pattern demonstration / no performance claim
What measurement should answer
Did the work become better, faster, or safer?
A useful measurement plan does not need a dramatic percentage. It needs an honest comparison that the team can repeat.
Define an accepted output
Set the source, test questions, citation standard, human correction, and failure behavior the result must meet.
Track what moved
Compare time, completion, correction, escalation, quality, risk, or capacity after people use the system.
The number needs a boundary
ROI is not a magic percentage on a landing page.
Count the right hours
Separate time removed, time shifted to review, and time created for higher-value work.
Count the corrections
An answer that is fast but needs constant repair is not the same as a useful accepted output.
Make avoided risk explicit
Document missing sources, access failures, unsupported answers, and incidents rather than claiming risk disappeared.
A measurement loop
Make the first pilot teach you what to measure next.
Name the unit of work
Choose a report, request, question, document, meeting, queue, or brief that repeats enough to compare.
Capture the baseline
Record current time, people, steps, errors, output, exceptions, and what good currently means.
Run the controlled workflow
Use a fixed question set, source, user group, approval path, and correction record during the pilot.
Decide whether to expand
Review evidence with the owner: keep, adjust, add a connector, expand users, or stop the workflow.
The strongest AI case study is not the biggest percentage. It is a clear before, a tested after, and an owner who can explain the difference.
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.
Can you promise a specific ROI?
No. We can help define the baseline, test set, and measurement plan. The result depends on the workflow, adoption, quality, and client context.
What should we measure first?
Choose the unit of work and record time, completion, correction, escalation, quality, or risk evidence that the owner already understands.
Is this only for large companies?
No. A small team can measure one queue, report, document set, or recurring question before deciding whether to expand.
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 baseline
What should this workflow improve?
Tell us the current process, output, reviewer, time, errors, and evidence leadership would trust.