Flox Intelligence Uses Edge AI to Keep Wildlife Away From Trains, Airports and Roads

The problem is costly and widespread. The FAA estimates that wildlife strikes cost U.S. civil aviation about $272 million a year on average between 1990 and 2025, according to TechCrunch. In France, rail operator SNCF says wandering animals affect more than 8,000 trains across the country each year and are among its five leading causes of delays. In Brittany, 120 trains hit animals in 2023 alone, disrupting 660 services and causing more than 15,000 minutes of delays.

Sara Nozkova, who developed the system, was inspired by the damage to infrastructure and animals. After 13 years working in transportation and autonomous vehicles, she concluded that the answer was not a louder deterrent. "I was convinced the answer was not a louder deterrent," Nozkova told TechCrunch. She joined the AI lab at KTH Royal Institute of Technology in Stockholm and began working on a system that could change its deterrent responses based on what a nearby animal is doing and which species it is. That work became Flox Intelligence.

Flox's edge devices process data on-site rather than in the cloud. Like autonomous vehicles, they use perception systems to sense their surroundings, but the models are trained on wildlife behavior. A motion sensor wakes the device when it detects movement, triggering a camera that uses on-device models to identify nearby animals. The device then emits a species-appropriate sound to scare them away. Nozkova says the system learns from experience and varies its responses so animals do not become habituated to repeated signals.

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

Flox devices are deployed at airfields and airport perimeters; road and rail corridors, especially fence ends and crossings along wildlife corridors; national parks; agricultural land; urban areas; mining sites; and critical infrastructure such as electrical substations. The company sells edge units upfront and 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 such partner.

Flox faces competition. Robin Radar's Scarecrow uses species-specific distress calls to disperse birds and records activity, while iCHASE sells a system that detects birds with computer vision and targets them with a moving laser, adjusting its response as needed. Nozkova says Flox's moat is the breadth of the system and the field data it has collected, which she calls "ground truth on what actually makes a moose or a grizzly bear move safely."

"Physical AI is walking out of the factory and into the messy, alive outdoors," Nozkova says. "Every machine that operates outside — trains, trucks, drones, tractors, robots — will need to understand nature, and nature intelligence is the next layer of the perception stack."