AI evaluation on live data

Models are usually evaluated on samples, test sets or synthetic data. Real operations differ: data arrives incomplete, out of order or in forms the test set never contained, and behaviour on the live workflow is what matters.

Putting an unproven model straight into production is a risk few organisations accept. Building a separate environment that mirrors production is slow and expensive.

A Data Mediation point already sees the live workflow’s data in motion. In Listen Only it can pass the same data, shaped by policy, to a candidate model and record what the model would have decided, without changing anything the workflow does.

The model’s decisions are compared with current outcomes on real operational data. When the evidence supports it, the same point moves to Active and the model starts to influence the workflow, one bounded step at a time. The decision rests on evidence, not on a demonstration.

• A candidate model evaluated on live operational data, without affecting outcomes
• Data shaped by policy before the model sees it
• Side-by-side evidence of model decisions and current outcomes
• A controlled path from Listen Only to Active

The exact scope, controls and evidence depend on the customer environment and are agreed before implementation.