Scalable Restaurant POS System
Production-ready POS system handling ~90 daily orders with real-time tracking and accurate billing.
Country
India
Industry
Resturant
Project Duration
2–3 months
Overview
A production-grade POS system designed to manage dine-in and takeaway orders efficiently.
The system is designed to handle real-world restaurant operations with a focus on reliability and efficiency.
Challenges & Solutions Provided
The Challenges
Restaurant operations were inefficient due to manual processes and lack of structured tracking.
- Frequent billing errors
- No real-time order visibility
- Slow service during peak hours
- Unstructured discount system
The Solutions
Developed a backend-driven system with clear workflows, centralized billing, and real-time tracking.
- Order lifecycle tracking
- Central billing engine
- Rule-based discount system
- Real-time order updates
Key Architecture Decisions
Snapshot Pricing
Stored item price at order time to prevent inconsistencies after price changes.
Centralized Discount Engine
Handled all discount logic in one place with caps and validation rules.
Stateless API Design
Ensured system can handle concurrent peak-hour traffic efficiently.
Project Flows
Order Lifecycle Flow
Customer places order (Dine-in / Takeaway)
Staff creates order
Items added with snapshot pricing
Discount applied
Billing calculated
Payment recorded
Status: CREATED → PAID → PREPARING → READY → DELIVERED
Discount Validation Flow
Discount applied
Validation checks (cart value, limits)
Discount capped and applied
Billing updated
Key Features
Order Management
Handle dine-in and takeaway orders with structured flow.
Billing Engine
Accurate calculation of totals and discounts.
Discount System
Flexible rule-based discount logic.
Real-Time Tracking
Track order status from creation to delivery.
Staff Roles
Role-based access for staff operations.
Analytics Dashboard
Track revenue, orders, and performance metrics.
Business Benefits
Reduced billing errors and manual corrections significantly
Improved coordination between staff and kitchen during peak hours
Enabled consistent order tracking across dine-in and takeaway operations
+30%
Order Processing Speed
+25%
Billing Accuracy
+20%
Peak Hour Efficiency
90+
Daily Orders Handled
Technology Stack
Next JS
Node JS
TypeScript
PostgreSQL
Redis
Stripe
AWS
Next JS
Node JS
TypeScript
PostgreSQL
Redis
Stripe
AWS
Next JS
Node JS
TypeScript
PostgreSQL
Redis
Stripe
AWS
Conclusion
This system transformed restaurant operations from manual and error-prone processes into a structured, reliable workflow. Earlier, billing inconsistencies, lack of order visibility, and peak-hour delays affected both service quality and efficiency.
