Satellite analytics, climate monitoring, and probabilistic forecasting for the global commodity supply chain.
Signal Feed
Climate signals, market analysis, and geospatial research from the coffee-producing belt.
Temporal coherence loss patterns detected six weeks ahead of official CONAB harvest assessment — and what it means for ICE futures.
Land Surface Water Index anomalies across the Central Highlands indicate below-average cherries — coinciding with tightening London futures spreads.
A technical walkthrough of our six-stage pipeline — from Sentinel-2 imagery ingestion to probabilistic price-range outputs for commodity desks.
Capabilities
Actionable intelligence combining climate signals, satellite analytics, and predictive modelling.
Producing Countries
Forecast Horizon
Spatial Resolution
01 · Commodity Focus
Purpose-built for Arabica with full architecture to expand across Robusta and emerging origins as demand evolves.
02 · Global Coverage
Continuous monitoring across 40+ producing nations — remote sensing, atmospheric models, and in-situ validation fused into one signal.
03 · Forecast Horizons
Probabilistic forecasting of yield instability, climate-driven supply disruption, and ICE/LIFFE futures volatility — up to six months ahead.
The Case for Geospatial
Global coffee production faces compounding exposure — climate volatility, supply-chain fragility, and environmental uncertainty are now permanent market forces. Our platform converts these signals into exploitable intelligence.
Early Detection
Detect environmental stress weeks before crop losses register in official data or consensus forecasts.
Price Anticipation
Anticipate futures volatility driven by satellite-observable climate anomalies ahead of market reaction.
Risk Quantification
Quantify long-term structural risk across yield, quality, and trade flow dimensions with probabilistic outputs.
System Architecture
Raw satellite imagery to actionable market intelligence — a four-stage, AI-enhanced pipeline operating at planetary scale.
Multi-sensor feeds — Sentinel-1/2, MODIS, LANDSAT, CHIRPS precipitation, ERA5 reanalysis, and in-situ weather networks.
Sentinel · MODIS · ERA5
Radiometric calibration, cloud-masking, atmospheric correction, spatial harmonisation, and statistical anomaly extraction.
NDVI · EVI · LST · LSWI
Deep-learning models fuse climate, vegetation, thermal, and market signals to generate probabilistic supply and price forecasts.
ML · Neural Networks
Market-ready indicators via dashboard, API, and intelligence briefs — formatted for commodity desks, analysts, and risk managers.
API · Dashboard · Reports
Who We Serve
Climate risk is a defining force across global coffee markets. Every stakeholder — from farm gate to trading floor — requires forward intelligence to protect margins and anticipate disruption.
Request Access →Identify climatic stress early, optimise crop management, and reduce yield uncertainty with predictive growing-season signals.
Forecast production shortfalls and regional quality shifts to secure supply, plan procurement, and mitigate logistics risk.
Gain early signals on price-moving climate anomalies, strengthening directional strategies and volatility positioning.
Protect sourcing portfolios, anticipate cost pressures, and strengthen long-term origin planning with climate-driven foresight.
Integrate geospatial climate risk metrics into pricing models, portfolio strategies, and commodity exposure management.
Monitor climate vulnerability, verify environmental compliance, and track resilience indicators across producing regions.
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