HyveGeo’s approach to restoring degraded land stands out at the FoodTech Challenge
Updated
January 21, 2026 11:09 AM
Clusters of sandstone buttes in Monument Valley, Colorado Plateau. PHOTO: UNSPLASH
HyveGeo, a climate-focused startup, has been named one of the global winners of the FoodTech Challenge, an international competition designed to surface practical technologies that strengthen food systems in arid and climate-stressed regions.
The FoodTech Challenge (FTC) is based in the UAE and brings together governments, foundations and agri-food institutions to identify early-stage solutions that address food production, land degradation and resource efficiency. Each year, hundreds of startups apply from around the world. In 2026, more than 1,200 teams from 113 countries submitted entries. Only four were selected.
HyveGeo stood out for its approach to one of agriculture’s hardest problems: how to make desert soil usable again. Founded in 2023 by a group of scientists and researchers, the Abu Dhabi-based company focuses on regenerating degraded land using a process built around biochar, a carbon-rich material made from agricultural waste, enhanced with microalgae. The aim is to accelerate soil recovery in environments where water is limited and land has been heavily stressed.
What caught the judges’ attention was not just the technology itself, but the way it links several challenges at once. The system turns waste into a usable soil input, reduces the time it takes for land to become productive and locks carbon into the ground instead of releasing it into the atmosphere. In short, it addresses land degradation, food production and climate pressure through a single framework.
As a winner of the FoodTech Challenge, HyveGeo will share a US$2 million prize with the other selected startups. Beyond funding, the company will also receive support from the UAE’s innovation ecosystem, including research backing, pilot projects, market access and incubation services to help move from testing into wider deployment.
The team’s plans focus on scaling within the UAE first. HyveGeo aims to work across Abu Dhabi’s network of farms and gradually expand into other arid and climate-stressed regions. Its longer-term target is to restore thousands of hectares of degraded land and contribute to carbon removal through soil-based methods.
Placed in a broader context, HyveGeo’s win reflects a shift in how food and climate technologies are being evaluated. Instead of chasing dramatic breakthroughs, competitions like the FTC are increasingly backing systems that connect waste, land, water and carbon into something usable on the ground. Not futuristic agriculture, but practical repair work for environments that can no longer rely on old farming assumptions. If that direction continues, the next wave of food innovation may be less about spectacle and more about quiet, scalable fixes for places where growing food has become hardest.
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Where smarter storage meets smarter logistics.
Updated
January 8, 2026 6:32 PM
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Kioxia's flagship building at Yokohama Technology Campus. PHOTO: KIOXIA
E-commerce keeps growing and with it, the number of products moving through warehouses every day. Items vary more than ever — different shapes, seasonal packaging, limited editions and constantly updated designs. At the same time, many logistics centers are dealing with labour shortages and rising pressure to automate.
But today’s image-recognition AI isn’t built for this level of change. Most systems rely on deep-learning models that need to be adjusted or retrained whenever new products appear. Every update — whether it’s a new item or a packaging change — adds extra time, energy use and operational cost. And for warehouses handling huge product catalogs, these retraining cycles can slow everything down.
KIOXIA, a company known for its memory and storage technologies, is working on a different approach. In a new collaboration with Tsubakimoto Chain and EAGLYS, the team has developed an AI-based image recognition system that is designed to adapt more easily as product lines grow and shift. The idea is to help logistics sites automatically identify items moving through their workflows without constantly reworking the core AI model.
At the center of the system is KIOXIA’s AiSAQ software paired with its Memory-Centric AI technology. Instead of retraining the model each time new products appear, the system stores new product data — images, labels and feature information — directly in high-capacity storage. This allows warehouses to add new items quickly without altering the original AI model.
Because storing more data can lead to longer search times, the system also indexes the stored product information and transfers the index into SSD storage. This makes it easier for the AI to retrieve relevant features fast, using a Retrieval-Augmented Generation–style method adapted for image recognition.
The collaboration will be showcased at the 2025 International Robot Exhibition in Tokyo. Visitors will see the system classify items in real time as they move along a conveyor, drawing on stored product features to identify them instantly. The demonstration aims to illustrate how logistics sites can handle continuously changing inventories with greater accuracy and reduced friction.
Overall, as logistics networks become increasingly busy and product lines evolve faster than ever, this memory-driven approach provides a practical way to keep automation adaptable and less fragile.