Maple AI Consultants

AI consulting case studies by Joel & Nanz Inc.

Food Service • 65 Events/Month

Case Study 35: Catering Company

Marketing-optimized case study for Canadian SMBs.

$98,000
Annual Savings
440%
ROI
2.9 months
Payback
Food Service • 65 Events/Month
Industry Focus

Executive Summary

Menu Planning: AI suggests menus based on event type, guest count, dietary restrictions, budget, and seasonal ingredient availability. Auto-generates shopping lists.

Challenge

Solution

  • Menu Planning: AI suggests menus based on event type, guest count, dietary restrictions, budget, and seasonal ingredient availability. Auto-generates shopping lists.
  • Quote Generation: Automated pricing based on menu selections, service style, event duration, and staff requirements. Generates professional proposals in minutes.
  • Staff Scheduling: Optimization algorithm assigns servers, chefs, and support staff based on event requirements, certifications, and availability.

Technical Stack

Key Metrics

24
Quote turnaround reduced from 24 hours to 2 hours
34%
Food cost percentage improved from 34% to 28%
27%
Event capacity increased 27% with same kitchen staff
85%
Staff scheduling time reduced 85%
1
Eliminated 1 FTE event coordinator role ($52k savings)

Implementation Timeline

8 weeks including recipe database setup

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