This article explores how Procurize’s new Real‑Time Regulatory Intent Modeling engine uses AI to understand legislative intent, instantly adapt questionnaire responses, and keep compliance evidence accurate across evolving standards.

This article explores the novel integration of reinforcement learning (RL) into Procurize’s questionnaire automation platform. By treating each questionnaire template as an RL agent that learns from feedback, the system automatically adjusts question phrasing, evidence mapping, and priority ordering. The result is faster turnaround, higher answer accuracy, and a continuously evolving knowledge base that aligns with changing regulatory landscapes.