Flox Intelligence Is Building AI to Keep Wildlife Away From Trains, Airports and Roads

Flox's edge devices can identify animals and use species-specific sounds to keep them away from critical infrastructure.

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When I was eight years old, I remember our train to Mumbai stopping with a lot of noise. When we started moving again, eight hours later, someone pointed out a broken tail, of all things, hanging from a branch near the rail.

You see the train had apparently hit a wild bison at full speed and the impact damaged the engine so much that it had to be towed for repairs. For a long time I thought that such things happen only in rural India, but a few years ago I realized that wildlife and infrastructure do not mix anywhere on the planet.

The FAA estimates that wildlife strikes cost US civil aviation an average of $272 million per year between 1990 and 2025. In France, rail operator SNCF says stray animals affect more than 8,000 trains a year across the country and are one of the top five causes of delays. In Brittany, in 2023 alone, 120 trains hit animals, causing disruption to 660 services and more than 15,000 minutes of delay.

Reading about all that damage, to both infrastructure and animals, inspired Sarah Nozkova (pictured above, left) to create a wildlife deterrent system that, unlike sirens, lights, fences, hawks, and carnage, is used to keep animals off roads, trains, tracks, airports, and other infrastructure.

"I'm convinced the answer is no longer a deterrent," he told TechCrunch.

After spending 13 years working in transportation and autonomous vehicles, Nozkova had learned how quickly the systems we build to navigate roads and other controlled environments fail when nature enters the equation.

"We've taught machines to be brilliant, but only in the environments we've designed them for," he said. "Cities, factory lines, warehouses. Fixed geometry, known objects. Stepping into nature, I saw firsthand how those same machines quickly go blind. Because nature is complex and ever-living."

So instead he joined the artificial intelligence lab at the KTH Royal Institute of Technology in Stockholm and began working on a system that could change its inhibitory responses based on what an animal was doing nearby and even what animal it was in.

This work evolved into Flox Intelligence, which spun out of KTH in 2020 and is a Startup Battlefield 200 finalist at TechCrunch Disrupt. (The company held a panel of VC judges on Tuesday at Disrupt, which this year runs at Moscone West in San Francisco through Thursday, Oct. 15.)

Flox builds edge devices that process data on-premises, not in the cloud. Like autonomous vehicles, they use perception systems to sense their surroundings, but they are trained on wildlife behavior. A motion sensor wakes up the device when it detects it and activates a camera that uses models on the device to detect nearby animals. The device then emits a sound appropriate to the species to scare them.

Nozkova says the system also learns from experience and changes its responses so animals don't get used to repeated signals.

The company currently sells devices that run on batteries and can be mounted on poles, trees and other structures. It also offers a software platform that shows customers where devices are deployed and what is happening on the ground. The platform can also generate reports for regulatory compliance and applications such as biodiversity monitoring. The long-term goal is to make the software portable enough to run on machines that operate outside, including trains, cars and drones.

Nozkova says there are about 150 Flux devices in North America, Europe and Australia in places including airports and airport environments. road and rail corridors (especially the ends of fences and crossings along wildlife corridors); national parks; agricultural land; urban areas; mining sites; and critical infrastructure such as power stations.

The company sells edge units up front, then charges an annual software and AI subscription after the first year. Flox also has OEM partnerships with companies that pay an annual fee to deploy its software on vehicles such as trains. Train manufacturer Alstom is one of these partners.

Nozkova said the company expects to end 2026 with revenue of about $1.5 million.

As unique as Flux's product and approach is, the startup is not without competition. Scarecrow Robin Radar also uses the species' distracting calls to disperse birds and record activity, while iCHASE sells a system that detects birds with computer vision, targets them with a moving laser, and adjusts its response as needed.

Nozkova says her moat is the breadth of the system and the data Flux has collected, which she calls "the truth about what really makes a moose or a grizzly bear move safely."

"Physical AI is moving out of the factory and into the dirty, living space," says Nozkova. Any machine that works outside—trains, trucks, drones, tractors, robots—must understand nature, and nature intelligence is the next layer of the understanding stack. Almost nobody makes it.

The company has so far raised about $5 million in pre-seed and seed rounds, with the seed round led by Unconventional and Tilia Impact Ventures. Co-investors in the round include GENIUS NY, Norrsken, Satgana and angel investors, Nozkova said.

The company is now opening a $10 million Series A, which is mostly aimed at scaling from about 150 devices to several thousand deployed units and expanding the infrastructure beyond current wildlife uses.

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