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DineSync: Restaurant Management Platform

An integrated restaurant management platform with AI-powered inventory forecasting that reduced food waste by 40% and streamlined operations across 22 locations.

Author
Advenno Team
May 11, 2026 Case Study
Client
DineSync Hospitality Group
Industry
Food & Beverage

An integrated restaurant management platform with AI-powered inventory forecasting that reduced food waste by 40% and streamlined operations across 22 locations.

The Challenge

DineSync was losing an estimated $420,000 annually to food waste from over-ordering and poor inventory rotation. Order errors averaged 8.3% due to handwritten tickets and miscommunication between front-of-house and kitchen. Each location used a different POS system, making consolidated reporting impossible. Average ticket time during peak hours exceeded 28 minutes, driving negative reviews and repeat customer loss.

  • $420,000 annual food waste from inaccurate inventory management and over-ordering
  • 8.3% order error rate due to handwritten tickets and verbal kitchen communication
  • 22 locations on 5 different POS systems with no consolidated reporting capability
  • Average peak-hour ticket time of 28 minutes, 40% above their target of 20 minutes
  • No data-driven menu engineering — pricing and item selection based on chef intuition alone

Our Solution

Advenno delivered a unified restaurant management platform featuring a modern cloud POS, digital kitchen display system with intelligent order routing, AI-powered inventory forecasting that predicts demand by day and daypart, and comprehensive analytics that enable data-driven menu engineering and labor optimization.

  • Cloud-based POS with tablet ordering, table management, and real-time menu updates across all locations
  • Kitchen display system with intelligent order routing, timing, and priority management
  • AI inventory forecasting predicting ingredient needs by location, day, and daypart with 93% accuracy
  • Menu engineering analytics identifying high-margin items and optimal pricing strategies
  • Labor scheduling optimization based on predicted covers and historical staffing patterns

Our Approach

1

Operations Immersion

Spent 2 weeks embedded in 3 representative locations across all dayparts — breakfast, lunch, dinner, and late-night — documenting every workflow from food prep to bill settlement.

2

Unified POS Design

Designed a flexible POS system that could accommodate the different workflows of their casual dining, fast-casual, and bar concepts while maintaining a unified backend for reporting.

3

KDS & Kitchen Integration

Developed the kitchen display system with intelligent routing that sends items to the correct station, manages cooking sequence for simultaneous table delivery, and tracks ticket times in real-time.

4

AI Inventory Engine

Built the demand forecasting engine using historical sales data, weather, local events, and seasonal patterns to predict ingredient needs and generate automated purchase orders.

5

Phased Multi-Location Rollout

Deployed to 3 pilot locations first, refined based on staff feedback, then rolled out to remaining 19 locations in groups of 4-5 over 8 weeks with dedicated on-site support.

The Results

Food waste dropped by 40% within 4 months, saving $168,000 annually. Order accuracy improved from 91.7% to 98.6%, and average peak-hour ticket time dropped from 28 to 18 minutes. The unified platform finally gave management real-time visibility across all 22 locations, and menu engineering analytics drove a 12% improvement in average check size by optimizing item placement and pricing.

40%
Reduction in Food Waste
98.6%
Order Accuracy (from 91.7%)
18min
Peak Ticket Time (from 28min)
12%
Increase in Average Check Size

Technologies Used

React
Node.js
PostgreSQL
Python
Socket.IO
Stripe Terminal
AWS
Docker

The kitchen display system alone was a game-changer — no more shouting, no more lost tickets. But the inventory AI is what keeps me up at night in a good way. We're ordering exactly what we need, when we need it.

Carlos Mendez - COO, DineSync Hospitality Group
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