LoopX
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About
LoopX is a comprehensive Physical AI platform specifically engineered to transform mining operations by unifying safety protocols and productivity metrics into a single, integrated system. Unlike disparate software solutions, LoopX focuses on the intersection of digital intelligence and physical machinery, providing mining sites with the tools necessary to monitor environments in real-time. The platform's primary purpose is to reduce operational risks while simultaneously identifying inefficiencies in the production cycle, ensuring that safety does not come at the expense of output. By bridging the gap between raw data and physical action, it helps operators maintain a safer and more predictable workspace. The core functionality of LoopX revolves around its sophisticated detection and tracking capabilities. Using Physical AI, the system provides real-time identification of personnel, vehicles, and potential hazards within the mining area, allowing for immediate reaction to prevent accidents. On the productivity side, the tool automates the logging of load counts, machine cycle times, and overall equipment utilization. This data is then aggregated into AI-powered dashboards, which offer stakeholders a clear, data-driven view of site performance, enabling them to make informed decisions based on live operational metrics rather than historical estimations. This platform is ideally suited for mining site managers, safety officers, and operations directors who require a holistic view of their industrial environment. It is particularly valuable for large-scale mining operations where manual tracking of equipment and safety compliance is complex and prone to human error. By providing a centralized source of truth for both safety events and production data, LoopX helps diverse teams—from ground-level operators to executive leadership—align their goals and improve the overall bottom line through reduced downtime and improved safety records. What distinguishes LoopX from other industrial AI tools is its clear path toward autonomy and its focus on Physical AI. Many competitors offer either safety monitoring or productivity analytics, but few integrate both into a scalable architecture that grows with the site's needs. LoopX is designed to be future-ready, meaning a facility can start with basic safety tools and gradually upgrade to assisted control and eventually full autonomous operation without needing to overhaul their entire technology stack. This modular approach to digital transformation provides a lower barrier to entry for mines looking to modernize.
Pros & Cons
Integrates both safety and productivity into one unified platform.
Provides real-time reaction capabilities for detecting people and vehicles.
Automates data collection for loads and cycle times, reducing manual errors.
Offers a clear scaling path from safety tools to full autonomy.
Features dedicated AI dashboards for data-driven operational decisions.
Pricing is not publicly listed and requires a custom quote.
Implementation likely involves significant hardware and sensor integration.
The tool is highly specialized for the mining industry rather than general industrial use.
Use Cases
Mining safety officers can monitor real-time hazard detections to prevent accidents involving personnel and vehicles on-site.
Operations managers can use automated load and cycle tracking to optimize machine utilization and reduce production bottlenecks.
Site executives can leverage AI-powered dashboards to make long-term investment decisions based on actual machine performance data.
Industrial engineers can scale the platform from basic monitoring to assisted control and eventual full autonomous operation.
Platform
Features
• real-time hazard detection
• physical ai integration
• scalability to full autonomy
• ai-powered data dashboards
• machine utilization monitoring
• cycle time analysis
• automatic load tracking
• vehicle and personnel identification
FAQs
What is Physical AI in the context of LoopX?
Physical AI refers to the integration of advanced AI models directly with physical mining hardware to enable real-time detection and reaction. This allows the system to perceive environmental hazards and manage machine movements dynamically on the site.
How does the platform improve mining productivity?
The system automatically tracks critical metrics such as load counts, cycle times, and machine usage rates. These insights are displayed on AI-powered dashboards to help managers identify bottlenecks and optimize machine utilization.
Can LoopX be used for autonomous mining operations?
Yes, the platform is designed to be future-ready and highly scalable. It can transition from providing basic safety alerts and tracking to supporting assisted control and eventually full machine autonomy.
What kind of hazards does the system detect?
The platform provides real-time detection for people, vehicles, and various site hazards. This ensures that both human operators and automated systems can react quickly to prevent collisions or dangerous incidents.
Pricing Plans
Enterprise
Unknown Price• Real-time hazard detection
• Vehicle and personnel tracking
• Automatic load counting
• Cycle time monitoring
• AI-powered dashboards
• Machine use analytics
• Scalable autonomy features
• Safety reaction alerts
Job Opportunities
Machine Learning Engineer
Optimize mining safety and operational efficiency with a Physical AI platform that automates hazard detection, load tracking, and site-wide performance analytics.
Benefits:
Competitive salary and benefits
Opportunity to work on cutting-edge autonomous technology
Mission-driven team environment
Dynamic and collaborative workplace
Growth potential
Education Requirements:
Bachelor’s degree in statistics, mathematics, computer science, computer systems engineering, or a related field
Master’s degree in machine learning, data science, or related quantitative field (preferred)
Experience Requirements:
Programming experience is required
Experience in statistical modeling is required
Experience in machine learning is required
Other Requirements:
Experience with computer vision and perception (2D/3D detection, SLAM/localization, sensor fusion)
On-edge/embedded deployment and performance optimization
Familiarity with ROS/ROS2, Git, Linux, PyTorch/NumPy, and SQL
Clear written and verbal communication skills
Previous working experience in the mining industry (preferred)
Responsibilities:
Implement cutting-edge techniques in machine learning and deep learning
Perform large-scale experimentation to evaluate model performance
Create advanced algorithms such as regression, simulation, and neural networks
Build automated pipelines for data cleaning, labeling, and quality assurance
Develop AI models for mining autonomy and collision-avoidance systems
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