The PaleoTech Platform

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.

AtmoSPHERE — Atmospheric Moisture & Hydrological Behaviour Engine

AtmoSPHERE™ analyses atmospheric moisture drivers, circulation context, climate-state signals, land–surface properties, and hydrological behaviour to estimate soil and surface moisture conditions across paddocks, subregions, and regions.

OceanWATCH — Ocean Boundary State & Circulation Context Engine

OceanWatch™ analyses large-scale ocean boundary conditions and circulation signals — including basin-scale temperature structure, current systems, overturning circulation indicators, and ocean–atmosphere coupling metrics — to characterise background oceanic constraints and drivers relevant to regional and global climate behaviour.

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.

PhaseX — Regime-State Signal Engine

Detects regime transitions across climate, ocean, and atmosphere by synthesising physical drivers, tilt anomalies, mass-flow perturbations, and state-shift signatures.
Models ENSO behaviour using physical signals, tilt anomalies, wind-state patterns, and Pacific-state dynamics.

WindPulse — Atmospheric flow-state detection

Jet-stream behaviour, regional flow structures, and atmospheric momentum interactions that influence rainfall patterns, ENSO development, and volatility.

RainMAP — Rainfall Reconstruction & Hydrological Coherence

Reconstructs rainfall behaviour, seasonal deviations, hydrological risk windows, and regional signatures.

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.

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.
Our Flagship Farm-ready companion with capital management, 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

Provides the adaptive intelligence layer that learns from PaleoTech’s physics-driven signals to enhance forecasts and regime detection.

SignalEngine — Adaptive AI Signal Layer

Synchronises multi-timescale signals from all physics and climate modules into unified phase windows.

PatternEngine — Analogue Discovery Engine

Identifies historical and repeating climate–soil–atmosphere structures to enhance seasonal foresight.

ForecastEngine — Seasonal Outlook Optimisation Layer

Transforms raw physics and climate signals into actionable seasonal forecasts.