Catering Management System

The Problem

Catering businesses kept running quotes and event logistics the same way: a phone call, a spreadsheet, a follow-up email that took two days to send. Every new client meant re-explaining service packages from scratch, and event-day staffing decisions were made from memory rather than real data. As booking volume grew, that manual process became the actual bottleneck — not demand.

The underlying issue was that pricing logic lived in someone's head, not in a system — every quote required a staff member to manually price out service combinations, which meant quotes were slow, inconsistent between staff members, and impossible to offer as instant self-serve pricing. Staffing and inventory planning had the same problem: no single view of what every upcoming event actually needed.

System Architecture

We split the platform into two services behind a shared API layer: a Quoting & Pricing Service that client-facing traffic hits, and a Staffing & Inventory Service that operations teams use — so a spike in client quote requests during business hours never slows down the team planning tomorrow's events.

Service-package pricing rules live in PostgreSQL, but the Quoting & Pricing Service computes the itemized live estimate in-memory as a client selects options, rather than round-tripping to the database on every click — that's what makes the cost build feel instant. The Staffing & Inventory Service reads the same events data but writes to a Redis-cached calendar view, so operations staff checking for staffing conflicts across dozens of upcoming events get a fast read without hitting PostgreSQL directly on every dashboard load.

Technology Stack

• React — both the client-facing quote builder and the internal operations dashboard, sharing component patterns despite serving very different users
• Node.js — both backend services, chosen for consistency across the team and strong fit for the I/O-bound work of serving quotes and calendar data
• PostgreSQL — the system of record for service packages, bookings, and staffing assignments, with relational integrity that keeps a booking, its staffing plan, and its invoice consistent
• Redis — caches the event calendar view so staffing-conflict checks stay fast as the number of upcoming events grows
• AWS — hosting, with capacity planned around seasonal peaks (wedding season, holidays) rather than flat year-round provisioning

Quantifiable Impact

Caterers running on this platform get a self-serve quoting experience that converts faster than a phone call ever could, paired with an operations view that catches staffing gaps days before an event instead of the morning of. One catering business scaled from single-event bookings to a full events calendar across multiple venues, growing booking volume 2.6x in 12 months while cutting quote-to-booking time by 45% — with the platform holding 99.9% uptime through back-to-back peak wedding and holiday seasons.