Portion adjustment
Repeated leftovers on a high-volume dish gave a school kitchen team the confidence to cut default portion sizes, reducing waste on that dish by 31% within six weeks.
Impact & case studies
Proven School & Cafeteria Food Waste Reduction with AI
Smart Bin AI deployments have analysed more than 20,000 disposals across four continents, helping schools and cafeteria teams cut food waste by an average of 19.7% through targeted, dish-level action.
19.7%+
average waste reduction
20,000+
disposals analysed
10+
location deployments
4
continents reached
Deployment reach
Real deployments across schools, universities, and canteens.
Smart Bin AI has been deployed at international schools, university dining halls, and food service partners across Wales, Israel, Thailand, Singapore, Costa Rica, and Eswatini, proving cafeteria food waste monitoring works across menus, service styles, and diner cultures.
Menu evidence
Dish-level food waste comparisons separated genuinely unpopular recipes from over-serving and timing effects, letting chefs redesign the menu with evidence instead of guesswork.
Awareness campaigns
Baseline and follow-up data made student and diner-facing food waste campaigns measurable rather than anecdotal, with clear before/after numbers to report.
Before / after
A clearer operating conversation.
Before
“We think portions may be too large.”
Occasional observation, broad totals, and no reliable dish comparison.
After
“This dish leaves 24% more waste on Tuesdays.”
Consistent evidence, a testable action, and a measurable follow-up.
Want to see how the numbers look week to week? Explore the live sample food waste dashboard, learn more about the Smart Bin AI device and computer vision pipeline, or review the pilot and deployment pricing.