The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to empower organizations that are exposed to dynamic pricing – such as in the transportation, retail and e-commerce sectors - with affordable, automated revenue management tools that enhance pricing decisions and improve financial performance. Organizations in these sectors often lack the resources, data infrastructure, and expertise needed to implement advanced pricing strategies. This project aims to provide access to smart pricing technology by developing an artificial intelligence-driven platform capable of operating effectively in data-scarce and competitive environments. The broader societal impacts include strengthening small businesses and supporting the economies surrounding dynamic pricing sectors. The innovations in forecasting, optimization, and competitive analysis have potential applications across a range of sectors experiencing dynamic pricing, thereby offering the potential for substantial commercial impact. This Small Business Innovation Research (SBIR) Phase I project addresses the challenge of optimizing pricing decisions in dynamically priced market sectors with limited historical data and intense price competition. The research objectives are to develop (1) novel demand forecasting methods that combine observational data with lightweight online experimentation; (2) an automated competitor analysis engine using econometric and machine learning tools; and