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Optimizing lithium recovery with satellite-driven AI
A global lithium producer improved evaporation pond management by combining satellite imagery and AI to protect lithium concentration and reduce operational costs.
Yield
Lithium recovery
Cost
Reduced sampling
Control
Real-time insight
From manual pond monitoring to AI-driven lithium optimization
The client observed a decline in lithium concentration in final brine and relied on costly, manual field measurements to manage evaporation ponds.
Objectives
Restore lithium concentration levels, reduce operational costs, and enable remote, real-time monitoring of ponds.
Opportunity
Lithium evaporation ponds require precise control to avoid premature lithium precipitation, which directly impacts yield and profitability.
Driving Complex Global Transformations
Proven delivery overcoming complex multi-country business challenges
Key Challenges
Manual sampling was expensive and limited in frequency
Limited real-time visibility into brine composition and volume
Complex evaporation dynamics increased operational risk
Solution
Developed an AI-assisted optimization model using satellite imagery
Identified relevant spectral bands to infer brine volume and chemical composition
Trained models using historical satellite data paired with field measurements
Enabled remote, real-time monitoring to support pond management decisions
Impact
Higher recovery with lower cost
improved control over lithium concentration dynamics.
Reduced reliance on costly manual measurements.
Enabled proactive pond management through remote monitoring.
Established a scalable foundation for advanced lithium analytics.
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