airth Foresight - Advanced Predictive Modeling
airth Foresight is an advanced predictive modeling solution designed for geologists and mining professionals to improve resource model accuracy and operational efficiency.
By leveraging machine learning, it provides insights into grade qualities, ore-waste boundaries, and geological uncertainties. airth Foresight bridges the gap between resource and grade control models, enabling real-time reconciliation and actionable predictions that enhance decision-making and optimize mining operations.
Predict. Analyze. Optimize Mining.
AIRTH FORESIGHT
What is airth Foresight?
airth Foresight is an advanced predictive modeling solution designed for geologists and mining professionals to improve resource model accuracy and operational efficiency.
By leveraging machine learning, it provides insights into grade qualities, ore-waste boundaries, and geological uncertainties. airth Foresight bridges the gap between resource and grade control models, enabling real-time reconciliation and actionable predictions that enhance decision-making and optimize mining operations.
Who Utilizes airth Foresight?
Geologists
Professionals who need accurate predictions for resource modeling and ore-waste boundary definition.
Geoscientists
Specialists who interpret geological data and need to understand uncertainty in resource models.
Mine Planners
Teams responsible for strategic mine planning who need to evaluate resource model confidence.
Why airth Foresight?
Improve resource allocation with enhanced ore-waste boundary evaluations.
Boost operational efficiency through predictive analysis of grade qualities.
Minimize risk and uncertainty with model heat mapping and confidence balancing.
Streamline decision-making processes with real-time reconciliation and performance evaluations.
Key Features
Explore airth Foresight's comprehensive suite of features designed to improve resource model accuracy, enhance decision-making, and optimize mining operations.
Predictive Model Evaluation
Connect & Evaluate Models
Analyze and compare resource and grade control models using machine learning.
- Connect models to evaluate performance with real-time reconciliation
- Identify areas for re-evaluation to improve operational accuracy
Enhanced Grade Predictions
Forecast Operational Outcomes
Forecast operational outcomes with improved grade quality predictions.
- Analyze historical data to create representative grade forecasts
- Utilize predicted grades for better planning and operational sampling
Optimized Ore-Waste Boundaries
High-Resolution Evaluations
Refine blast designs and material separation accuracy with high-resolution boundary evaluations.
- Evaluate boundaries with greater detail than resource models
- Improve blast designs for optimized ore-waste separation
Advanced Reporting Tools
Insights & Performance Analysis
Gain insights into resource model performance and operational alignment.
- Generate performance reports to assess reconciliation results
- Identify areas for model re-evaluation and improvement
Confidence Balancing and Auditability
Risk & Uncertainty Management
Minimize risk with heat mapping and uncertainty analysis.
- Use heat maps to identify areas of low confidence
- Balance planning confidence to reduce operational risks
See airth Foresight in Action
Watch how airth Foresight enhances resource modeling accuracy, reduces uncertainty, and helps you make better operational decisions.
Improved Resource Allocation
Better define ore-waste boundaries to optimize resource allocation and reduce dilution
Enhanced Grade Quality Predictions
Make data-driven decisions with improved grade forecasting and modeling tools
Reduced Uncertainty
Identify and address areas of low confidence with heat mapping and model reconciliation
Ready to optimize your mining operations?
Increase productivity and stay ahead in the competitive mining industry by being among the first to benefit from our innovative predictive modeling solutions.
Improved Resource Allocation
Enhance ore-waste boundary evaluations for better resource allocation and reduced dilution.
Reduced Risk and Uncertainty
Minimize risk with model heat mapping and confidence balancing in resource models.
Enhanced Decision Making
Streamline decision-making with real-time reconciliation and performance evaluations.