AI

No model without an eval gate

How we stop a model reaching production before it proves it beats the one already there.

A model that looks better in a demo is not necessarily better for the user. What separates the two is a fixed evaluation set and a metric agreed before the experiment, not after it.

Every release here passes a gate: a set of examples from your own business, and a metric comparing the candidate against what is in production now. It does not pass unless it wins.

This costs a week of release time and prevents the silent regression nobody notices for a month.

Ready to start?

One free hour, and you leave with a scope, a cost range and a timeline.