I want to launch a fully-automated, browser-based laundry management system built around a clean, dashboard-style interface. The solution must cover our complete workflow—from the moment a customer places an order at shop counter/online to the final delivery and follow-up notification—while giving staff the real-time controls they need to keep operations tight. Core workflow I need covered • Order placement and live order tracking • Pickup & delivery scheduling with route status updates • Inventory and garment tagging control • Employee scheduling and productivity tracking • Billing, invoicing, and secure online payments • Central customer database with service history • Automated WhatsApp notifications at key stages • Visual reports and analytics for revenue, workloads, and inventory turns Key expectations • Web-only for this phase, fully responsive so it works smoothly on desktop, tablet, and phone browsers. • Modular codebase (preferably Node/React, Laravel/Vue, or similar modern stack) that lets us add a dedicated mobile app later without rewriting core logic. • Clean, role-based dashboard UI: separate views for admin, staff, and customers. • RESTful or GraphQL API to integrate with existing POS hardware and potential delivery partner apps. • Secure user auth (JWT or OAuth), GDPR-ready data handling, and audit logs. • Deployment on AWS, Azure, or GCP with CI/CD and automated backups. Deliverables 1. Source code in a private Git repo with clear README. 2. Staging URL for iterative testing, then production deployment. 3. Database schema and migration scripts. 4. Post-launch support window for critical fixes and onboarding assistance. Acceptance criteria • All listed features are accessible through the dashboard and function across Chrome, Firefox, Safari, and Edge. • Average page load under 3 s on a 4G connection. • 100 % of high-severity bugs resolved before hand-off. I’ll supply branding assets and detailed workflow charts once we kick off. If you have live demos of similar SaaS back-office systems, that will help accelerate selection.