About 150 Flox devices are operating across North America, Europe, and Australia, using cameras and on-device AI to identify nearby wildlife and play sounds tailored to the animal. The company is now opening a $10 million Series A, which would mostly fund expansion to several thousand deployed units and extend the system beyond its current wildlife uses.
Flox’s approach starts with a motion sensor. When it detects movement, a camera switches on and on-device models identify the animal. The device then emits a species-appropriate sound intended to scare it away. Flox says its system learns from experience and varies its responses so animals don’t become habituated to repeated signals.
That differs from the sirens, lights, fences, falcons, and culling traditionally used to keep wildlife away from roads, railways, airports, and other infrastructure. Sara Nozkova developed Flox’s deterrent after reading about the harm animal collisions cause to both infrastructure and wildlife. “I was convinced the answer was not a louder deterrent,” she told TechCrunch.
The problem reaches well beyond any one location. The FAA estimates that wildlife strikes cost U.S. civil aviation an average of about $272 million a year between 1990 and 2025. In France, rail operator SNCF says wandering animals affect more than 8,000 trains each year and rank among the country’s five leading causes of delays. In Brittany, animal collisions involved 120 trains in 2023, disrupting 660 services and causing more than 15,000 minutes of delays.
Nozkova spent 13 years working in transportation and autonomous vehicles. She said that experience showed her how quickly systems designed for controlled environments can fail when nature enters the equation. “We have taught machines to be brilliant, but only inside the environments we engineered for them,” she said. “Cities, factory lines, warehouses. Fixed geometry, known objects. Stepping outside into nature, I saw firsthand how the same machines quickly go blind. Because nature is complex and always alive.”
She later joined the AI lab at KTH Royal Institute of Technology in Stockholm to work on a system that could adapt its deterrent response to what an animal is doing and what species it is. Flox’s edge devices process data on-site rather than in the cloud. Their perception systems sense the surroundings, much like those used in autonomous vehicles, but are trained on wildlife behavior.
Flox currently sells battery-operated units that can be mounted on poles, trees, and other structures. Its software platform shows clients where devices are deployed and what is happening on the ground, and 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 outdoor machines, including trains, cars, and drones.
Nozkova says the roughly 150 deployed devices are used at airfields and airport perimeters, road and rail corridors, national parks, agricultural land, urban areas, mining sites, and critical infrastructure such as electrical substations. Along road and rail corridors, deployments are especially focused on fence ends and crossings along wildlife corridors.
The business 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 partner. Nozkova said Flox expects to end 2026 with about $1.5 million in revenue.
Flox is not without competition. Robin Radar’s Scarecrow uses species-specific distress calls to disperse birds and records their activity. iCHASE sells a computer-vision system that detects birds, targets them with a moving laser, and adjusts its response as needed.
Nozkova says Flox’s competitive moat is the breadth of its system and the field data it has collected, which she describes as “ground truth on what actually makes a moose or a grizzly bear move safely.” She argues that machines working outdoors will need to understand nature: “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. Almost nobody is building it.”
Flox has raised about $5 million across pre-seed and seed rounds. The seed round was led by Unconventional Ventures and Tilia Impact Ventures; co-investors across the rounds include GENIUS NY, Norrsken, Satgana, and angel investors, Nozkova said. The proposed $10 million Series A would mostly support growth from about 150 devices to several thousand deployed units, while extending the underlying system beyond its current wildlife use cases.
