Maximize Net Metal Production

Increase your net metal production in the most sustainable, efficient and safe way, using Scientific AI from IntelliSense.io to run your mine & plant at its optimum state.

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Scientific AI: Providing Real-Time Predictive Intelligence

Scientific AI is a breakthrough development in AI technology pioneered by IntelliSense.io that fuses together mechanistic (first principle or physics) models with Machine Learning techniques to uniquely provide real-time predictive intelligence. 

 

Mine-to-Market Process Optimization

Today’s mining workforce uses smart technology to empower their teams and attract tomorrow’s generation of mining professionals.

IntelliSense.io’s Scientific AI is designed to increase efficiency across the mining and processing journey, and has been perfected across multiple projects and customer sites. Our out-of-the-box application suite, designed by and for mining professionals, allows you to predict, simulate and optimize process outcomes.

Process Optimization Apps

Our process optimization apps can be deployed on a specific process or connected across the entire value chain.

They are powered by our Scientific AI Decision Intelligence Platform, brains.app.

Stockpile and Inventory Optimization

Stockpile & Inventory Optimization

Grinding Optimization App

Grinding Optimization

Thickener Circuit Optimization

Thickener Optimization

Flotation Circuit

Flotation Optimization

Solvent Extraction Optimization App

Solvent Extraction (SX) Optimization

Leaching Optimization App

Leaching Optimization

brains.app Decision Intelligence Platform

By collecting, cleaning, interpolating, and assimilating a federated data lake ready for AI, the brains.app platform powers a portfolio of process optimization apps targeting the mining value chain; resulting in accelerated value delivery in terms of increased throughput, recovery, and reduced energy, water, and waste footprint.

Real-Time Decision Intelligence Across the Mining Value Chain

IntelliSense.io uniquely combines expertise in Mining disciplines, Data Science, and Software Engineering with the power of Scientific AI to deliver real-time, process-specific optimization applications for the Mining Industry.
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Rapid Results and Fast Time-to-Value

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Deliver Sustainable Efficiency Gains

Our Scientific AI-powered apps can be used individually or combined together to achieve efficiency gains across your mine-to-market value chain.

One app

Optimize Individual Processes

Connect apps together

Optimize your Entire Value Chain

Discover our Case Studies

Enhancing Gold Production Using 3D Block Model of Stockpiles for Selective Mining

3D block models of stockpiles facilitated a selective mining strategy to increase gold recovery

THICKENER: Reduce Stoppages to Save $1-3M

Reduce Stoppage Events and Save $1.8M

Prevent high-torque stoppage events in Thickener’s process to save $1.8M and 22.000m3 of water

Decrease Plant Feed Variability

Decrease Plant Feed Variability by 5-8%

Improvements in the accuracy of mineralogical and geometallurgical information enabled better plant setup ($1,4M)

Increase Uranium Recovery

Increase Uranium Recovery by 3% ($25M)

Improving process control in Tails Leach Tanks with 18 new virtual sensors and optimization recommendations

Improve Overall Cu Recovery by 1% ($38M)

Improve Overall Cu Recovery by 1% ($38M)

Achieve a stable Flotation circuit by maximizing recovery per cell

3d Stockpile Inventory Accuracy

Improve Fe Accuracy by 32.7%

3D Stockpile outperforms the weighted average model with Fe accuracy improved by 32.7%

Preventing 20,000 Tonnes of Ore Deviation

Using Stockpile to map dump and load deviation events, ensuring 20,000 tonnes of ore was not lost

STOCKPILE: Identify 100k Tonnes of Waste in the RoM

Identifying 100,000 Tonnes of Waste in RoM Stockpiles

FMS data quality management was able to detect 100,000 tonnes of waste dumped in the wrong location

LEACHING: Reduce Acid Consumption by 5-8%

Reduce Acid Consumption by 5-8%

A case study in reducing fines, acid consumption and improving copper recovery

GRINDING: Increase Mill Throughput by 1%

Increase Grinding Throughout by 1%

A case study in increasing Grinding Circuit throughput and reducing mill stoppages

THICKENER: Decrease Flocculant usage by 16%

Decrease Flocculant Usage by 16%

Stabilize Thickener’s process to increase underflow % of solids while reducing flocculant by 16% & rake torque by 18%

FLOTATION: Increase $8M with Metal Recovery

Increase Metal Recovery by $8M

Achieve a stable Flotation circuit by maximizing recovery per cell

Increase Copper Mass Transfer

Increase Copper Mass Transfer by 3%

A case study in improving solvent extraction circuit stability to increase copper mass transfer by 3%

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