Answer from your material
Policies, contracts, working papers, code notes, and internal guidance can be searched through an approved source set.
Self-hosted AI / familiar interface, controlled system
The private ChatGPT alternative has to fit the work, not just resemble the interface.
We deploy a private assistant or workspace around the questions, documents, tools, and access rules your team actually uses. The runtime may be local hardware or a client-owned cloud; the right choice follows the workload, not the label.
Your documentsYour access rulesMeasured workloadAdmin handover
Pattern demonstration / runtime varies by client
What people actually want
The chat box is the visible part.
The valuable replacement is the controlled system behind it: sources, permissions, tests, and a team that knows what it owns.
Set the boundary
Choose who can see which projects, whether external inference is allowed, and what happens when the answer is not in the source.
Keep the workspace useful
The administrator receives the accounts, configuration, test record, update path, and known limitations needed to operate it.
Three ways to run it
Self-hosted does not always mean a server under the desk.
Client-owned cloud
A VM or private environment in an account the client owns, with a provider path and storage choice that are disclosed.
Approved region
Use a regional deployment when location, procurement, or provider controls matter more than local hardware.
On-premise runtime
Run retrieval or inference on local hardware when the no-external-inference requirement justifies the operational cost.
Before buying hardware
Measure the questions first.
Name the first tasks
Define what users ask, what sources answer it, how many people need access, and whether the output is read-only or a draft.
Choose the data path
Compare client cloud, regional, API-backed, and local options against the actual constraint rather than an imagined one.
Test the workload
Run real questions, document retrieval quality, latency, concurrency, cost, and failure behavior before sizing hardware.
Deploy and document
Configure the selected runtime, train the administrator, and record the accounts, limits, backups, and update process.
A self-hosted ChatGPT alternative is not a clone with a different logo. It is a company-owned answer path.
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.
Does self-hosted mean no API provider?
Not necessarily. A client-owned application and retrieval layer can still use an approved external model provider. The full data path must be written down.
Can you recommend the hardware?
Yes, after the workload is measured. Hardware, power, cooling, support, and model performance are part of the architecture decision, not an automatic first purchase.
Is this a fine-tuned model?
Usually not. Most first systems use retrieval, permissions, and workflow design over your material. Fine-tuning is a separate specialist choice.
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 workload
What should your private ChatGPT alternative answer?
Tell us the users, source material, privacy constraint, and first questions. We will help choose the runtime before the hardware.