food wastesustainabilityinventory optimization

Intelligent Food Waste Reduction & Sustainability System for Restaurants & Bars

Project Verdant

Client:

In-house product development

Duration:

10 months

Team:

2 systems architects, 2 data analysts, 2 full-stack engineers

The Problem

Restaurants and bars operate with limited visibility into waste patterns, making it nearly impossible to identify root causes—whether it's over-prepping, spoilage, portion inconsistency, or bar over-pouring. Without actionable data, waste reduction remains reactive rather than strategic, and sustainability goals stay aspirational.

What We Did

Built an intelligent waste tracking system integrated directly into kitchen and bar workflows. Developed ML-powered demand forecasting to optimize prep quantities, automated waste logging with category classification, bar yield modeling to detect over-pouring patterns, and spoilage prediction based on inventory age and temperature data. Created daily waste-risk dashboards with actionable recommendations for purchasing and prep teams.

Outcome

Achieved 28% reduction in food waste across pilot locations, reduced bar variance to 4% through yield tracking, and provided real-time waste insights that improved purchasing decisions and reduced over-ordering by 18%.

Operational Impact

Automated waste logging workflows. Predictive prep quantity recommendations. Real-time bar yield monitoring. Daily waste-risk summaries for decision-making.

Key Challenges

1

Inconsistent Waste Recording

Standardizing waste tracking across diverse kitchen and bar operations without disrupting fast-paced service workflows.

2

Predictive Model Accuracy

Building ML models that account for seasonality, events, and menu changes while maintaining forecast reliability.

3

Behavioral Change Integration

Designing a system that encourages consistent usage without adding friction to existing kitchen routines.

What Made This Work

Workflow-Integrated Tracking

Waste logging built directly into existing POS and kitchen workflows for seamless adoption.

ML-Powered Demand Forecasting

Predictive models reducing over-prep and purchasing waste through intelligent quantity recommendations.

Bar Yield Intelligence

Pour tracking and variance analysis identifying over-pouring patterns and optimizing inventory.

Spoilage Prevention

Age and temperature-based alerts preventing waste from expired or degraded ingredients.

Sustainability-First Design

Built around measurable waste reduction and operational efficiency for long-term environmental impact.