Insights

The distance between a working demo and a governed deployment is where AI programs stall. The Fast AI Deployment Framework is a method for closing that distance: establish baselines before building, assign every capability a risk tier, and place evaluation harnesses and human-approval controls around anything that reaches production. The result is speed with evidence: deployment moves quickly because the controls are designed in, not bolted on.

The framework sequences the work: connected foundations with source systems remaining authoritative; measurement infrastructure before capability; automation where baselines justify it; AI where evaluation can prove it. It is written for operators, not researchers, and it is the method running today in the production program on our Work page.