Question 1

Will my data be used to train models?

Accepted Answer

Enterprise API tiers do not train on your input by default, and we confirm this contractually. Where data is processed and how long it is retained is part of the architecture decision — a fully self-hosted setup is possible when required.

Question 2

What happens when the model is wrong?

Accepted Answer

That is a certainty, not a risk. So every setup includes three things: the source behind each answer is shown, there is a handoff path when the model is unsure, and output quality is continuously measured against an evaluation set. An AI feature you don't measure degrades silently.

Question 3

Are the running costs predictable?

Accepted Answer

Token cost scales with usage, so it is projected upfront and monitored. Caching, compact prompt design and routing to smaller models typically bring it down substantially. A usage dashboard ships with the first release.

Question 4

Which jobs are a poor fit for AI?

Accepted Answer

Calculations that demand exactness, decisions that must be explainable for compliance, and anything a simple rule already solves. We say so plainly during feasibility — we don't add AI where AI isn't needed.

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