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. 
Metal trays holding gray rocks and pale sand on a dusty workshop floor, with the middle tray of stones in sharp focus.
Yield
Lithium recovery
Cost
Reduced sampling
Control
Real-time insight
Excavator and loader work on a muddy forest road at dusk, moving rocks and logs as water splashes, with pine-covered mountains in the background.
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
Miners in hard hats drill into wet rock inside a dim underground tunnel, lit by warm lamps and blue shadows, with machinery and ore carts on rails beside them.
Manual sampling was expensive and limited in frequency
Close-up of metallic blue and silver mineral crystals with sharp facets, glittering highlights, and a softly blurred brown background.
Limited real-time visibility into brine composition and volume
Industrial pipes span a rocky canyon; one pours blue water into a rushing river while another carries glowing orange molten material with sparks.
Complex evaporation dynamics increased operational risk
Solution
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Developed an AI-assisted optimization model using satellite imagery 

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Identified relevant spectral bands to infer brine volume and chemical composition 

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Trained models using historical satellite data paired with field measurements 

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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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