Wildlife encounters can disrupt transport and harm animals as well as infrastructure. Flox Intelligence is taking a different approach to reducing them: its devices identify nearby animals and respond with sounds chosen for the species, rather than relying only on fixed barriers or generic alarms.
Responding to animals in the field
Flox was founded by Sara Nozkova after she spent 13 years working in transportation and autonomous vehicles. She saw that machines designed for controlled settings can struggle in natural environments, where conditions and animal behavior are less predictable.
Instead of making a deterrent louder, Nozkova pursued a system that could adapt its response to what an animal is doing and which species is present. That work began at the AI lab at KTH Royal Institute of Technology in Stockholm. Flox spun out of KTH in 2020.
The company’s devices process information on-site, at the edge, rather than sending it to the cloud. A motion sensor activates a camera, and on-device models identify nearby wildlife. The unit then emits a sound intended to scare the animal away. According to Nozkova, the system also varies its responses so animals are less likely to become accustomed to repeated signals.
Where the devices are used
Flox sells battery-operated units that can be mounted on poles, trees and other structures. Its software platform lets clients see where devices are deployed and what is happening at those locations. It can also produce reports for regulatory compliance and support biodiversity monitoring.
Nozkova says about 150 devices are active in North America, Europe and Australia. Deployment sites include airfields and airport perimeters, roads and rail corridors, national parks, agricultural land, urban areas, mining sites and electrical substations.
Road and rail corridors are among the intended settings, particularly fence ends and crossings along wildlife corridors. These places can create points where animals and transport routes meet, making a location-specific deterrent useful to operators.
A broader role for outdoor AI
Flox’s longer-term plan is to make its software portable enough to run on machines that work outdoors, including trains, cars and drones. The company already has original equipment manufacturer partnerships with firms that pay an annual fee to use its software on vehicles. Train manufacturer Alstom is one partner.
The business also sells edge units upfront and charges an annual software and AI subscription after the first year. Nozkova said the company expects to end 2026 with revenue of about $1.5 million.
The company is not alone in wildlife deterrence. Robin Radar’s Scarecrow uses species-specific distress calls to disperse birds and records activity. iCHASE detects birds with computer vision and targets them with a moving laser, adjusting its response as needed.
Nozkova describes Flox’s advantage as the breadth of its system and the data it has collected in the field. That data, she says, provides “ground truth on what actually makes a moose or a grizzly bear move safely.”
Funding plans and next steps
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 company is opening a $10 million Series A. It expects the funding to go mostly toward growing from about 150 devices to several thousand deployed units and extending the system beyond its current wildlife use cases.
That ambition places wildlife detection within a wider question for outdoor automation: how can machines respond safely when the environment is alive and changeable? Flox’s current product focuses on deterring animals near infrastructure, while its planned software expansion would bring that understanding to more kinds of machines operating outside.