Along the way, the project developed GrizCam, an AI-powered multisensory recording unit that captures panoramic video, spatial audio, and real-time species detection in the most remote and rugged terrain on earth. That technology now serves four interconnected conservation goals: advancing field science by giving biologists unprecedented tools to study elusive wildlife; incenting private landowners to steward habitat through automated, AI-verified wildlife monitoring — and helping reduce predator-livestock conflicts through science-backed acoustic deterrence; combating wildlife crime by giving enforcement agencies real-time detection and geolocation of illegal activity in the field; and building the digital wild by creating immersive connections between people and the natural world. The moonshot is to decode wolf communication as fully as humanly possible — and in doing so, build something with the potential to transform terrestrial conservation across the globe.

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Wildlife is often monitored using trail cameras, but increasingly "sound" is proving to be a more effecient approach. Passive Acoustic Monitoring (PAM) is a cost-effective, noninvasive method for surveying wolves, often outperforming camera traps in detection probability. Wolves are loud...think "car horn" loud...so they can be heard from miles away. While bioacoustic monitoring isn’t new, modern hardware as well AI advances in software have significantly reduced costs and boosted productivity in telemetry work. We follow the ethical framework outlined by the NYU MOTH Program.