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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Why investors are backing Applied Brain Research’s on-device voice AI approach.
Updated
January 14, 2026 1:38 PM
Plastic model of a human's brain. PHOTO: UNSPLASH
Applied Brain Research (ABR), a Canada-based startup, has closed its seed funding round to advance its work in “on-device voice AI”. The round was led by Two Small Fish Ventures, with its general partner Eva Lau joining ABR’s board, reflecting investor confidence in the company’s technical direction and market focus.
The round was oversubscribed, meaning more investors wanted to participate than the company had planned for. That response reflects growing interest in technologies that reduce reliance on cloud-based AI systems.
ABR is focused on a clear problem in voice-enabled products today. Most voice features depend on cloud servers to process speech, which can cause delays, increase costs, raise privacy concerns and limit performance on devices with small batteries or limited computing power.
ABR’s approach is built around keeping voice AI fully on-device. Instead of relying on cloud connectivity, its technology allows devices to process speech locally, enabling faster responses and more predictable performance while reducing data exposure.
Central to this approach is the company’s TSP1 chip, a processor designed specifically for handling time-based data such as speech. Built for real-time voice processing at the edge, TSP1 allows tasks like speech recognition and text-to-speech to run on smaller, power-constrained devices.
This specialization is particularly relevant as voice interfaces become more common across emerging products. Many edge devices such as wearables or mobile robotics cannot support traditional voice AI systems without compromising battery life or responsiveness. The TSP1 addresses this limitation by enabling these capabilities at significantly lower power levels than conventional alternatives. According to the company, full speech-to-text and text-to-speech can run at under 30 milliwatts of power, which is roughly 10 to 100 times lower than many existing alternatives. This level of efficiency makes advanced voice interaction feasible on devices where power consumption has long been a limiting factor.
That efficiency makes the technology applicable across a wide range of use cases. In augmented reality glasses, it supports responsive, hands-free voice control. In robotics, it enables real-time voice interaction without cloud latency or ongoing service costs. For wearables, it expands voice functionality without severely impacting battery life. In medical devices, it allows on-device inference while keeping sensitive data local. And in automotive systems, it enables consistent voice experiences regardless of network availability.
For investors, this combination of timing and technology is what stands out. Voice interfaces are becoming more common, while reliance on cloud infrastructure is increasingly seen as a limitation rather than a strength. ABR sits at the intersection of those two shifts.
With fresh funding in place, ABR is now working with partners across AR, robotics, healthcare, automotive and wearables to bring that future closer. For startup watchers, it’s a reminder that some of the most meaningful AI advances aren’t about bigger models but about making intelligence fit where it actually needs to live.