By Blake Jackson
Ficio, a startup founded by Youhanna Meleka, M.Eng. ’26, is developing artificial intelligence technology designed to improve food handling across the supply chain, from identifying fruit defects in orchards to automating food preparation in commercial kitchens.
The company’s platform is designed to operate across different machines and applications. Its early products, FieldSorter and FicioPrep, aim to help farmers and food service operators improve efficiency, reduce waste, and make better use of food resources.
FieldSorter uses computer vision to identify apples with defects, including bruises, punctures and clipped stems, while moving through orchard rows.
The technology allows growers to evaluate fruit quality during harvest instead of waiting months for assessments after controlled storage.
It also records individual apple grades and connects the information to the trees where the fruit originated, providing useful data for orchard management.
“Growers spend a lot of time and money finding out which apples are market-ready and which aren’t,” Meleka said. “We’re helping them make that determination at harvest rather than months later in a packing house.”
Ficio demonstrated FieldSorter at Cornell AgriTech in Geneva, New York, earlier this year to approximately 300 growers.
The company is collaborating with farms in Ontario and Wayne counties while preparing additional field trials and improving the technology based on farmer feedback.
FicioPrep applies the same AI platform to commercial food preparation. Designed for large-scale dining operations, the robotic station identifies ingredients, evaluates potato quality, and prepares potatoes into fries or chips. Future capabilities could include handling additional vegetables, preparing ingredients on demand, and cleaning the machine internally.
“The vision is food prepared fresh, on demand, rather than a person chopping large quantities of food hours in advance,” said Meleka, who demonstrated FicioPrep to managers at Cornell Dining to continue gathering feedback on the prototype.
“It would also keep track of how much food is being processed, providing kitchen managers with data about their operations.”
Meleka's interest in reducing food waste stems from his childhood in Cairo, Egypt, where he witnessed food scarcity. His experience in logistics and manufacturing, including studies at Pennsylvania State University and work as a global supply manager at Tesla, helped shape his approach.
Ficio's broader goal is to develop machines capable of picking, sorting, packing and preparing food through FoodMind, a foundational AI model designed to adapt across different machines and environments.
“The beauty of FoodMind is that we built the software to be hardware-agnostic, so it can work across different applications,” Meleka said. “We originally developed it for food preparation in restaurants, but since it’s a foundational model that is learning across different body morphologies, it can adapt to different tasks without having to start from scratch each time.”
Supported by Cornell's entrepreneurship network, Rev: Ithaca Startup Works, Universal Robots and NVIDIA's Inception program, Ficio continues refining its technology with input from farmers and industry partners.
Photo Credit: ficio
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