Organizations considering ARI should be able to understand how Prairnova approaches security, privacy, AI and customer information without having to decode a technical white paper.
Here are the questions we expect thoughtful buyers to ask.
Questions about how ARI uses, protects and keeps customer information separate.
No. ARI is being designed to use the information needed for the intended outcome. The information required depends on the customer environment, product capability and agreed scope.
It is not intended to. Customer information is designed to remain associated with its organization rather than becoming general knowledge available across other customers.
Not by default. Materially different use would require appropriate governance and customer consideration.
Prairnova will document hosting and processing arrangements for the deployed service. We will not make permanent residency or sovereignty claims before verifying the production service.
Questions about how ARI uses AI, what it can and cannot do, and where people remain responsible.
No. AI can help organize and explain information; material organizational decisions remain with authorized people.
No. AI output does not create new authority. Access is intended to remain controlled independently of model-generated instructions.
No. It can misunderstand context or work from incomplete information. Important outputs should remain open to supporting-evidence review.
Questions about access control, customer boundaries and how ARI and Prairnova handle security.
ARI is being designed around identifiable users, appropriate authentication and least privilege. Exact controls depend on deployment and customer configuration.
Access should be limited to authorized operational or support purposes. Details are covered through controlled security processes.
ARI is being designed around customer boundaries. Detailed isolation architecture and evidence belong in a controlled review.
Questions about supporting information, explainability and decision context.
That is a core design principle. ARI is being designed so users can review relevant information behind important priorities and conclusions.
No. Users should be able to understand why something deserves attention without needing internal algorithms or proprietary product logic.
No. Completion and demonstrated improvement are not necessarily the same thing. ARI is being designed to review current evidence rather than assume success.
Questions about Microsoft environments, other integrations and required permissions.
No. Those products continue doing their operational work. ARI is being built to make better use of relevant information.
No. Microsoft is the initial evidence ecosystem, not the intended boundary of the platform.
It depends on the connection and product stage. Connection-specific requirements can be discussed during onboarding or security review.
Questions about current capabilities, planned functionality and product maturity.
ARI is being developed and validated through controlled early-access engagements. Availability and limitations will be described according to their actual stage.
Not necessarily. Connections not ready for customer use will be labelled according to their actual stage.
Prairnova will not claim certification before it has been achieved. Formal assurance may be pursued as customer demand and maturity justify it.
Some questions are best answered in a more detailed conversation.
Security, privacy and resilience are a shared effort.
If your organization has a security, privacy, AI, residency or procurement requirement that is not answered here, talk to us. We would rather address the actual requirement than make a broad claim that may not apply to your environment.
