A technology company has developed what it describes as the first continuous intelligence system designed specifically for rare earth mining and processing operations, addressing what its founders identify as a fundamental gap between data generation and human decision-making capacity in complex industrial environments.
Sabian Global Inc. licenses Sabian Technology, an AI-driven platform that processes live operational data across mining, processing, and refining environments to deliver what the company calls decision intelligence. Unlike traditional analytics tools that work retrospectively or focus on isolated processes, the system is designed to function across entire operations simultaneously while conditions are actively unfolding.
The platform distinguishes itself through its delivery method. Rather than requiring continuous screen interaction or manual data interpretation, Sabian Technology delivers intelligence through podcast-format audio briefings, allowing operators and engineers to receive updates without stopping their work to analyze dashboards or reports.
Jason Wallace, co-founder and CEO of Sabian Global Inc., originated the concept after observing a recurring pattern in modern mining sites. Operations generate vast amounts of sensor data and process information, but human teams struggle to interpret it all as systems grow more interconnected and complex. “We used to spend time trying to understand what was happening. Sabian tells us while it’s happening,” according to an operations executive from a mining environment who has worked with the system.
Wallace partnered with Shaquille Campbell, a software engineer with over 20 years of experience building production-grade systems for large corporations, to develop the technology. Campbell focused on ensuring the platform could operate reliably within live industrial environments at scale, while Wallace shaped the system’s requirements based on real-world mining conditions.
The intelligence platform includes multiple product modules, each addressing specific operational domains while functioning as part of a connected system. STRATA, a solvent extraction stability engine, analyzes conditions in rare earth hydrometallurgy plants to detect instability that can lead to organic loss, off-spec product, or unplanned shutdowns. The module examines phase imbalance, mass-transfer disruption, and upstream variability across interconnected extraction, scrubbing, and stripping circuits.
RECLAIM ENGINE addresses tailings management by assessing recoverable rare earth value in waste streams, ponds, and legacy deposits. The platform models recovery scenarios, economic potential, and environmental considerations, repositioning tailings as potential secondary orebodies rather than simply waste material requiring disposal.
A third module, PREDICTUS, forecasts ore quality, plant performance, and instability risk across crushing, grinding, flotation, leaching, and solvent extraction processes. The system provides early identification of conditions that could result in throughput loss or recovery reduction, supporting coordination between mine planning and plant operation.
The company positions these modules as components of a unified system rather than standalone tools, emphasizing that the platform connects data across mining, processing, and refining stages to provide operators with a coherent view of their entire operation.
One site manager involved in pilot deployment noted the shift in operational approach: “Sabian works live. That’s the difference.” A senior technology executive from the public sector offered a similar assessment: “Other tools give you noise. Sabian gives you what matters — and nothing else.”
Wallace has been outspoken about the broader implications of AI in industrial settings, rejecting what he considers misplaced concerns about automation and employment. “People were born with judgment, curiosity, responsibility, and purpose. Work was supposed to serve that — not replace it,” he has stated. He argues that the relevant question is not whether AI will eliminate jobs, but whether organizations will continue requiring humans to perform tasks that machines can handle more effectively.
“The fear isn’t that AI will take jobs. The fear is that people have confused their job with their identity,” Wallace said, adding that “AI can replace tasks. It cannot replace purpose.”
The company has focused its initial deployment on rare earth operations due to what it describes as the sector’s operational complexity and strategic importance. Rare earth mining involves intricate chemistry, process variability, and high-consequence decision-making where suboptimal performance has material financial and strategic impact.
Sabian Global Inc. licenses the technology to mining and processing organizations as a deployed software system, providing ongoing operation of the platform as an intelligence service rather than a one-time software installation.
The company describes its achievement not as incremental improvement to existing tools, but as the establishment of what it calls a new category of industrial intelligence infrastructure. According to testimonials from early partners, the platform has provided visibility that was previously unavailable. “It’s the first system we’ve seen that can read the whole operation at once,” a technical lead in processing and refining reported.
By combining continuous data processing, cross-operational analysis, and voice-native delivery, the company has positioned itself at the intersection of AI development and industrial application, specifically targeting environments where human attention cannot scale to match system complexity.