PaleoTech is a physics-driven, data-backed, multi-layer intelligence platform that turns planetary signals into climate and agricultural decisions. It does this by unifying 4 tightly integrated layers — from deep-Earth physics to farm-scale outcomes — into a single coherent system designed for accuracy, early detection, and real-world usability.
Where conventional systems begin with weather models, PaleoTech begins at the source of climate itself: Earth’s tilt, rotation, and energy flows. From this foundation, the platform builds upward through climate interpretation, agricultural planning, hazard detection, and an adaptive AI backbone that evolves continuously.
The PaleoTech Platform Flow Diagram
1. Core Physics Engines
The Core Physics Layer is the deepest tier of PaleoTech. It captures Earth’s fundamental motions, energy flows, and momentum transfers — forming the base signals that power all downstream climate, hazard, and agriculture modules.
PaleoIQ — Climate-State Engine (Primary Core)
The foundational physics-driven engine that reconstructs and interprets large-scale climate behaviour using axial tilt, ENSO dynamics, orbital mechanics, mass flow and long-lead system signals. Everything in PaleoTech either feeds into PaleoIQ™ or is powered by it.
AxisPulse — Axial Tilt & Wobble Monitoring
Real-time tilt, wobble, polar motion, and obliquity-energy signatures.
MassFlow — Planetary mass & circulation dynamics
Atmospheric and oceanic mass flow, angular momentum, circulation, and global momentum anomalies.
2. Climate Engines
The Climate Layer translates PaleoTech’s physics signals (tilt, rotation, mass flow) into actionable climate-state intelligence: ENSO regimes, rainfall phases, atmospheric behaviour, ocean conditions, and seasonal windows. These engines form the middle tier of PaleoTech — between physics and agriculture.
ESNOLink — ENSO Regime Detection & Forecasting
Models ENSO behaviour using physical signals, tilt anomalies, wind-state patterns, and Pacific-state dynamics.
RainMAP — Rainfall Reconstruction & Hydrological Coherence
Reconstructs rainfall behaviour, seasonal deviations, hydrological risk windows, and regional signatures.
WindPulse — Atmospheric flow-state detection
Jet-stream behaviour, regional flow structures, and atmospheric momentum interactions that influence rainfall patterns, ENSO development, and volatility.
TempMAP — Temperature outlook engine
Provides temperature reconstructions and forward outlooks built from PaleoTech’s underlying climate-state signals.
3. Agricultural Engines
The Agriculture Layer transforms climate-signal intelligence into seasonal planning, risk windows, paddock-level behaviour, and farm-ready outputs. These engines sit directly above Climate Engines and are the outward-facing intelligence used by farmers, agronomists, and demonstration farms.
MoistureMAP — Soil Moisture Reconstruction & Hydrological Behaviour Engine
Analyses climate-state signals, rainfall reconstruction, soil profiles, and regional hydrological behaviour to estimate soil moisture conditions across paddocks and regions.
SoilSYNC — Soil–Climate Synchronisation & Field-State Intelligence
Connects soil-condition indicators with climate-state signals to produce interpretable insights on field readiness, planting windows, operational constraints, and sub-surface behaviour.
CropCAST — Seasonal Climate Intelligence for Agriculture
Farm-ready companion with rainfall outlooks, climate windows, volatility profiles, ENSO phase assessments, and operational guidance for agronomy.
4. AI & Signal Engines
The AI & Signal Layer unifies all physics-driven signals across PaleoTech into a single adaptive intelligence framework. It performs real-time regime detection, anomaly scoring, seasonal signal alignment, system-state interpretation, and forecast optimisation. This is the core analytical brain of the platform
PaleoAI — AI-Driven Intelligence Layer
SignalEngine — Adaptive AI Signal Layer
PatternEngine — Analogue Discovery Engine
ForecastEngine — Seasonal Outlook Optimisation Layer