Sarcouncil Journal of Engineering and Computer Sciences

Abstract: This article presents a conversational AI framework for Configure, Price, Quote (CPQ) platforms that addresses persistent challenges in sales quoting processes. Despite their essential role in modern sales organizations, CPQ systems often present usability barriers through complex configuration dependencies, intricate pricing rules, and technical interfaces that impede user adoption and productivity. The proposed framework embeds domain-specific language models within CPQ environments to enable natural language interactions that guide users through configuration workflows, resolve errors, and provide contextual product information. The architecture integrates core components, including an NLP engine, a configuration knowledge base, and an error resolution system with existing CPQ platforms through standardized APIs. Evaluation results demonstrate improvements in onboarding efficiency, error reduction, and quote completion speed, with particularly strong benefits for new users and complex product scenarios. The article explores implementation considerations, quantitative and qualitative assessment methodologies, and a strategic roadmap for future development incorporating emerging AI technologies.