The Future of Mining, Together

Modern mining faces a persistent data gap between geological models and operational reality, leading to critical inefficiencies, revenue loss, and risk. Stellatus closes this gap by transforming unknown variables into actionable, data-driven certainties.

Explore Our Solutions

Autonomous Solutions for a Safer, More Productive Mine

Autonomous monitoring system for tailings dam integrity

Autonomous Tailings Dam Integrity Monitoring

Problem: Tailings dam failures represent mining's gravest catastrophic risk, with the 2019 Brumadinho disaster costing Vale $7 billion. Regulators and investors demand rigorous monitoring to meet the Global Industry Standard on Tailings Management (GISTM) by August 2025, but current methods provide insufficient internal visibility.

Solution: Our robotics-as-a-service solution deploys autonomous monitoring systems to continuously assess dam health through advanced subsurface and surface analysis, providing intelligent risk assessment and early warning alerts without assuming liability for dam safety.

Prevent catastrophic failures through unprecedented internal stability data.
Achieve GISTM compliance with continuous, multi-sensor monitoring.
Build the world's largest tailings behavior dataset for predictive analytics.

Autonomous drone scanning a blasted ore face to create a grade map

Real-Time Ore Face Characterization

Problem: Misidentifying ore and waste costs mines millions annually through dilution and ore loss. With declining ore grades, the need for precise grade determination at the face has never been more critical to maintain margins in a competitive market.

Solution: Our autonomous platform provides instantaneous ore grade and mineralogy analysis directly at the mining face through advanced sensing technology, enabling real-time segregation of ore from waste with minimal human intervention.

Reduce dilution by up to 20% and recover previously lost ore.
Optimize mill feed grade to improve energy efficiency and throughput.
Deliver data-driven decisions that maximize recovered metal value.

Robotic inspection system for mill liner wear monitoring

Mill Liner Wear Optimization

Problem: Grinding mills are the "heartbeat" of mineral processing plants, but unplanned liner failures cause catastrophic downtime costing $500,000–$1,000,000 per hour. Traditional maintenance errs on caution, replacing liners early and wasting economic life while risking unexpected failures.

Solution: Our robotic inspection service operates during planned maintenance stops, using advanced scanning technology to create precise 3D liner wear maps. Predictive models determine remaining liner life and recommend optimal replacement timing, eliminating surprises while maximizing liner utilization.

Prevent unplanned mill shutdowns and extend liner life optimally.
Reduce maintenance costs through data-driven replacement schedules.
Improve plant reliability and throughput predictability.

Ground robot patrolling a conveyor line to predict idler failures

Conveyor Belt Health Monitoring

Problem: Conveyor systems are critical to material transport, but idler failures can cause belt rips leading to multi-day outages costing millions. Manual inspections of thousands of components are dangerous, time-consuming, and often miss early warning signs of failure.

Solution: Autonomous monitoring systems continuously patrol conveyor lines, detecting component degradation, belt misalignment, and other issues before they cause catastrophic failures, enabling predictive maintenance scheduling.

Eliminate unplanned conveyor downtime and prevent belt fires.
Extend conveyor component life through early intervention.
Enhance worker safety by automating hazardous inspections.

Analytics system monitoring heap leach pad performance

Heap Leach Pad Analytics

Problem: Heap leaching leaves billions in recoverable metal "on the table" due to inefficient solution flow, channeling, and dry zones. Poor monitoring leads to incomplete recovery, environmental risks from leaks, and wasted water and reagents in arid mining regions.

Solution: Our advanced monitoring platform provides internal visibility into heap leach pad performance, mapping solution flow patterns, identifying inefficiencies, and optimizing irrigation strategies for maximum metal recovery.

Increase metal recovery by optimizing leach solution distribution.
Reduce water and reagent consumption in water-scarce regions.
Prevent environmental incidents through early leak detection.

AI system optimizing flotation circuit performance

Real-Time Flotation Optimization

Problem: Flotation circuits are often run by intuition rather than data, leading to suboptimal recovery rates. A 1% drop in recovery can cost tens of millions annually, while reagent overuse wastes money and reduces performance in an era of declining ore grades.

Solution: Our AI-powered platform uses real-time process data to continuously optimize flotation parameters, maximizing metal recovery while minimizing reagent consumption through intelligent process control.

Boost metal recovery by 1-2% through optimized flotation control.
Reduce reagent costs by 5-10% while maintaining performance.
Improve circuit stability and response to feed variations.

Autonomous drone mapping hazardous underground stopes and voids

Underground Stability Analytics

Problem: Falls of ground are a leading cause of underground fatalities and costly production interruptions. Current geotechnical data collection is sporadic and subjective, leaving dangerous instabilities undetected until failures occur.

Solution: Our autonomous scanning platform creates detailed 3D maps of underground excavations, continuously monitoring ground conditions and providing intelligent recommendations for support optimization and hazard prevention.

Prevent rockfalls through proactive ground support recommendations.
Improve geotechnical decision-making with comprehensive data.
Enhance worker safety in high-stress underground environments.

Our Approach: From Data to Decision

Autonomous Data Capture

We deploy ruggedized drones and ground robots to safely and consistently collect high-fidelity data from the most critical and hazardous areas of your operation.

AI-Powered Analytics

Our cloud platform processes this data, creating dynamic digital twins and running predictive models to transform raw information into clear, actionable intelligence.

Actionable Insights

We deliver insights, not just data. Our system provides simple, clear recommendations that integrate into your existing workflows, empowering your teams to make safer, more profitable decisions.

About the Founder

Hi—I'm Mike Ochs, former Field CTO at Microsoft and now Distinguished AI Architect at Siemens. For 11 years I've taken AI and robotics from prototype to production in mission-critical, regulated environments—turning messy, real‑world data into reliable, auditable decisions. I build systems that fuse sensors, autonomy, and cloud/edge inference, integrate cleanly with existing workflows, and deliver measurable ROI. If you have a challenge, I can help you solve it with AI, safely and at scale.

This background maps directly to Stellatus's core initiatives: advanced sensing and analysis for real‑time ore characterization; predictive analytics for critical equipment monitoring; comprehensive digital modeling for proactive infrastructure integrity; and autonomous navigation systems for hazardous area mapping. The common thread is disciplined engineering that moves from data to decision—fast.

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Let's explore how an autonomous pilot program can de-risk your operations and deliver a powerful return on investment. Reach out to schedule an introductory call.