Your data stays yours. Every number stays explainable.
Paradygma was built to reconcile two requirements that are usually traded off against each other: the security standards implemented by IT functions, and the speed a business needs. Here is how.
Security
Three ways to deploy, depending on your constraints.
They differ on where your data sits and who runs the model. Nothing else changes, and in all three the data stays in your environment.
On-premise or on your own cloud
A sovereign technology stack, open and auditable. An offline option is available for your most sensitive data.
SaaS on your private instance
Access through a secure web interface with strong authentication. Hosting is provider-agnostic. Your data remains entirely yours.
Full Service
The SaaS option, with your data and your model maintained by our teams on the cloud provider of your choice. You keep ownership of the model and data and can take it back at any time.
Data ownership
Your data is yours
We do not hold it, we do not copy it outside your environment, and we have no rights over it.
Your model is yours
The ontography built during an engagement is your asset. Documented, exportable, and it stays with you whatever happens to the commercial relationship.
Your data is never used to train anything
Not our models, not anyone else's, not in aggregate, not anonymised. There is no clause anywhere in our contract that permits it. Use of LLMs is under your contractual agreements with the provider.
Auditability
Every result is auditable
Every scenario can be traced back to the source data that fed it and the business rules that produced it.
No hallucination
Your decision criteria, your business rules and your operational knowledge are written explicitly into the Ontography layer. They are not learned implicitly by a statistical model. This is a difference in kind, not in degree.
Deliberately not a black box
An opaque model asks you to trust a result. Paradygma lets you rebuild it. An executive can challenge a scenario in the meeting. An auditor can redo it line by line.
Governance
Today the most consequential modelling in your company lives in unversioned, unaudited spreadsheets held by two people. Bringing it into a versioned, permissioned, documented environment is a risk reduction before it is a capability gain.
Roles and permissions
Who can read a model, who can change a constraint, who can publish a scenario.
Version control
Every change to the model is recorded and reversible.
Traceable changes
Who changed which hypothesis, when, and what it moved.
Documented models
The ontography is readable by someone who did not build it. A design requirement, not a by-product.
Continuity and reversibility
Source code escrow
Your model and your ability to run it do not depend on our continued existence.
Documented reversibility
Model and data are exportable in a documented format. The exit path is written down before you start, not negotiated after.
Contractual pilot exit
The first engagement has a defined end and a defined exit. You are not committing to a platform in order to answer a question.
European technology
Built on open foundations, with no dependency on any technology provider for the operation of your model.