Imagine a smart trash can that knows exactly what you're throwing away. It uses a camera and a scale to identify food waste automatically, like a digital accountant for your kitchen scraps. Instead of guessing why food is wasted, chefs get a clear report telling them exactly how to buy less and save more.
Restaurants and hotels waste 15% of all food production but lack the tools to track this waste. This leads to lost profits and a high ecological footprint.
A plug-and-play hardware kit combining a smart camera and scale with AI image recognition software for automatic food waste registration.
If you are a hotel chain dealing with high buffet waste — this project developed a smart camera and scale system that can decrease food waste levels by up to 70%. This allows your kitchens to save over €30,000 annually.
If you are a restaurant group dealing with low profit margins — this project developed an AI recognition tool that can increase net profit margins by up to 3%. It automatically registers waste to optimize kitchen inefficiencies.
If you are a commercial caterer dealing with unpredictable food ordering — this project developed a system that integrates with external ordering systems to pre-fill them based on actual waste data.
The product is offered as a Product-as-a-Service for a monthly fee with no upfront costs. Based on available project data, this model removes the initial financial barrier for professional kitchens.
The hardware is designed as a plug-and-play product that clients can install in under 30 minutes. It features remote fleet management and customer success tooling to support large-scale deployments.
Based on available project data, the core technology consists of proprietary AI computer vision food recognition algorithms and integrated hardware (smart camera and scale).
The system integrates with external restaurant ordering systems to pre-fill orders based on waste insights. It is designed to be non-intrusive to the guest experience.
Based on available project data, an average kitchen can save over €30,000 annually, suggesting a rapid return on the monthly service fee.
The project is led by a single SME, ORBISK BV from the Netherlands, which maintains 100% industry control. This lean structure, consisting of 24 specialists including engineers and data scientists, allowed for rapid iteration of the hardware and AI algorithms without the complexity of academic partnerships.
Contact ORBISK BV in the Netherlands
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