Enterprise AI

Routing saves money only when you measure cost per resolved task, and that number depends on who decides what "resolved" means.

As AI moves from advising to acting, organizations face a harder question than adoption: who is actually accountable when something goes wrong?

Transitioning AI from prototype to production reveals that the true challenges lie not in the model itself, but in the surrounding ecosystem—data pipelines, user behavior, governance, and trust. Success demands resilient systems designed for messiness and unpredictability.