An AI-Enabled Low-Code CRM Architecture For Intelligent Fuel Booking And Predictive Inventory Management

This paper proposes an Artificial Intelligence (AI)–enabled cloud-based CRM architecture developed on the Salesforce platform to modernize gas station operations through intelligent automation and predictive analytics. The system integrates fuel booking, inventory management, supplier coordination, and customer interaction into a unified digital platform. AI techniques including time-series forecasting, anomaly detection, and customer behavior analytics are embedded to transform operational data into predictive insights. Machine learning models analyze historical transactions to forecast fuel demand, optimize inventory levels, and detect abnormal operational patterns. Salesforce automation tools such as Flows and Apex triggers enforce business rules, while AI-driven dashboards provide real-time predictive decision support. Experimental evaluation demonstrates improved forecasting accuracy, reduced operational errors, faster transaction processing, and enhanced managerial decision-making. The proposed architecture demonstrates how AI can elevate traditional CRM systems into intelligent, scalable, and proactive operational platforms suitable for multi-branch fuel retail environments.