TL;DR
A specialized reinforcement learning evaluator that grades each individual step of an AI model's reasoning path rather than just the final outcome.
Unlike traditional outcome-based evaluators, a process reward model analyzes intermediate logic, step-by-step calculations, and thought transitions. This granular approach prevents reward hacking and ensures the model does not arrive at a correct final answer via incorrect or hallucinated reasoning. It typically serves as an external verifier during search-based inference, selecting or pruning candidate pathways as reasoning unfolds.
Why this matters for your business
By validating the logical journey alongside the final answer, process reward models make multi-step AI reasoning substantially more reliable, safe, and explainable.
