Train–score feature compilation pipeline
What buyers should infer
Keeps training and downstream scoring aligned on the same engineered fields so exported rows match what the model was fitted on.
Commercial fit
Typical companion inside Batch ML Systems scopes—engineering the artefact trains and cron jobs both honour before we discuss API serving or monitoring add-ons.
Reference overview
A batch compilation step turns approved raw extracts into a versioned feature table under locked column contracts. Fit and score both load the same built artefact so transforms cannot silently diverge across environments.
Handoff notes
Useful when you treat reliability as engineering: rejects bad batches early, validates schema and duplicates, and can expose a thin HTTP helper for inspecting transforms—not a sprawling vendor feature platform. Fits buyers who already buy into batch-first ML milestones.