ml platform

An ML platform is the internal system that lets many teams build and ship models reliably. What matters is naming the components (data, features, training, registry, serving, monitoring) and arguing why standardizing beats per-team reinvention, plus when not to build.

A platform that no one uses is wasted headcount; a platform built too early is premature. What matters is justifying the investment by leverage and designing a paved path teams adopt willingly. Here is the framing.