Dineflow ERP: An Advanced Industry-Grade Solution for Optimised Restaurant Management

Abstract

Managing a food-service establishment involves constant negotiation between perishable inventory, fluctuating customer demand, and narrow profit margins. Despite these pressures, a substantial fraction of independent restaurants in India continue to rely on isolated point-of-sale terminals that provide no decision-support for procurement, workload forecasting, or shift scheduling. This paper introduces DineFlow ERP, a cloud-native, microservice-based enterprise resource planning platform engineered exclusively for restaurant environments. The system unifies the complete order lifecycle, kitchen-order-ticket (KOT) dispatch, table and floor coordination, live inventory tracking, payroll processing, and contactless QR-based guest ordering within a coherent three-tier architecture. A dedicated Predictive Intelligence layer integrates Ridge Regression and Random Forest for short-horizon demand forecasting; a Collaborative Filtering engine combining Singular Value Decomposition (SVD) with the Apriori association-rule algorithm for personalised menu recommendations; a Log-Log Ordinary Least Squares (OLS) dynamic pricing module; and a Heuristic Waste Predictor aligned with UN SDG Target 12.3. Identity and access management is enforced through Auth0, RS256-signed JSON Web Tokens, and AES-256-CBC client-side encryption distributed across five role-based access control (RBAC) personas. A live production deployment recorded 98 % module completion, a 7.6 % MAPE on stable SKUs via Random Forest, a 23.4 % reduction in procurement over-ordering, and zero critical OWASP vulnerabilities.