The platform functions by plugging directly into existing control networks, bypassing the need for extensive hardware overhauls. It utilizes three layers of AI—edge vision for material classification, vision-language models for contextual interpretation, and conversational agents for execution—to process chaotic material streams at millisecond speeds. According to CEO R. Paul Singh, the technology aims to capture the 93% of raw materials currently lost to landfills, effectively turning waste streams into reliable domestic supply chains.

Navigator targets critical efficiency gaps, claiming to boost facility throughput by up to 30% while identifying equipment anomalies before they trigger costly shutdowns. The software also simplifies compliance with complex Extended Producer Responsibility (EPR) regulations by tracking recovery rates and material composition. Early adopters, including Caglia Environmental, report that the system replaces manual operational guesswork with immediate, data-driven decision-making. EverestLabs has integrated the platform into broader industrial ecosystems, collaborating with partners such as Schneider Electric and Pellenc ST to bridge the divide between legacy operational technology and modern, AI-driven automation.