Building Reliable RLHF Pipelines

Reinforcement learning from human feedback is only as good as the feedback itself. Noisy, inconsistent labels produce noisy, inconsistent models.

Calibration first

Before any production labeling begins, evaluators are trained against gold-standard examples and measured on agreement rates. Calibration turns subjective judgment into a repeatable signal.

QA by design

Every batch passes through spot checks, consensus review, and senior escalation for ambiguous cases — so the preference data you train on is trustworthy.