AI/ML

From Pilot to Platform: Operationalizing AI/ML

JCJames Carter · VP Engineering

January 8, 2026 10 min read

From Pilot to Platform: Operationalizing AI/ML cover image

The pilot-to-platform gap is wide and expensive. Closing it requires investment in five areas: data foundations, evaluation, observability, governance, and developer experience.

A pilot proves the science. A platform makes the science repeatable.

Teams that win invest 60% of their AI/ML budget in platform infrastructure within the first 18 months.

Tags:

MLOps

Strategy

Platform

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From Pilot to Platform: Operationalizing AI/ML

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Ready to ship something users love?