Design and implementation of a smart quotation system

Abstract

We propose the design and development of an Automated Quote Evaluation (called AQE) system that semi-automates the quoting process for equipment sales and services. Various machine learning tools (linear and nonlinear regression algorithms, automated feedback module, tagging, feature scoring) are used in order that AQE generates consistent, accurate and timely quotes. Preliminary validation is provided in the context of a case study with Ciena (global supplier of telecommunications networking equipment, software and services). Therein, AQE issues quotes for performing network equipment operations and planning the required technical human resources in order to install the equipment in customer networks.