What separates a demo from something people use
A great deal of AI spending buys a demonstration. It works on the sample data, impresses in the meeting, and quietly stops being used within a quarter because nobody trusts it on the awkward cases.
We start from the opposite end: what decision is being made today, how often, by whom, and what it costs when it is wrong. If a model cannot beat that baseline we will tell you before you spend anything. When it can, we build it to be monitored — because a model that was accurate at launch and has not been checked since is a liability wearing a dashboard.
