An invitation to explore what's possible when autonomous biosensor swarms, edge AI, and 50 years of geological data converge with the world's most ambitious copper growth strategy.
Each sensor contains synthetic metalloproteins engineered for specific ion binding. When target ions contact the sensor, conformational changes trigger UV-Vis fluorescence—unique spectral signatures for each element.
Units form self-healing mesh networks. Data hops between nodes to reach cellular/satellite gateways. 1,000+ unit swarms cover 500km² with 99.7% uptime.
The probe's microchannels use capillary action to draw soil moisture upward without pumps. Dissolved mineral ions travel with the water to the biosensor chamber. Works in any soil with >5% moisture.
Dissolved mineral ions enter the sensor chamber. Hyperlogatrine proteins have engineered binding pockets with precise geometry matching specific ion sizes.
When a target ion binds, the protein undergoes a conformational shift—changing its 3D structure, enabling energy transfer.
UV excitation triggers characteristic fluorescence at specific wavelengths. Cu emits at 450nm, Li at 520nm, Co at 580nm.
Fluorescence intensity is directly proportional to ion concentration. GeoNeuron™ AI outputs ppm/percentage readings.
Our neural network is trained on the largest proprietary geological dataset ever assembled—soil samples from known deposits worldwide, correlated with drill-verified assay results.
Each element produces a distinctive UV-Vis fluorescence pattern when bound to Hyperlogatrine. Our library contains 47 elements across 200+ geological contexts.
| METRIC | TRADITIONAL | HYPERLOG |
|---|---|---|
| Cost per km² | $25,000+ | $12,000 |
| 10,000m drilling | $2.7-3.6M | Pre-validated |
| Exploration phase | 12+ years | 6-8 weeks |
| Discovery rate | <1% | 87%+ |
Multiple engagement models to match Glencore's priorities and risk appetite.
We're not proposing a transaction—we're proposing a conversation.
What could Hyperlog's stack do for Glencore's most ambitious projects?