From AI pilot to production platform
A practical path from a promising AI experiment to a reliable, governed product.
An AI demo proves that a model can produce an interesting answer. A production product must prove much more: that the answer is useful, repeatable, secure and economical in a real workflow.
Define the decision, not the model
Begin with the user decision or task the system should improve. Name the acceptable error, the human review point and the information that may enter the model.
Build an evaluation set
Collect representative cases, including difficult and unsafe ones. Run the same set whenever prompts, models or retrieval sources change.
Design the operating model
Production AI needs access controls, traceable inputs, cost monitoring and a fallback when confidence is low. Assign owners before release.
Release narrowly, learn deliberately
Start with one valuable workflow. Observe corrections, latency and adoption, then expand only when the evidence supports it.
