Finance

GeonatIQ develops AI systems for financial services that sit at the intersection of markets, policy, and real assets, with a strong focus on commodities and capital allocation.

We build numerical commodity price prediction models across energy, minerals and metals, and carbon markets. These models are designed to operate over multiple time horizons and market regimes, supporting trading, hedging, and long-term strategic decisions. A core feature of this work is the integration of language-based models that read and interpret news, policy announcements, and macro events in context, rather than as raw sentiment. Instead of reducing articles to positive or negative polarity, our systems extract structured signals such as expected price direction, magnitude, time horizon, and volatility impact, and align these contextual embeddings with underlying numerical price models. This approach improves forecasting and decision-making in policy-driven and energy-linked markets.

Alongside market models, we build AI agents that automate complex financial workflows. Our Capital Raising Agent continuously identifies, qualifies, and prioritises investors across commodities and real assets by interpreting mandate signals, timing, and behavioural indicators in real time. It is grounded in live capital raising activity rather than static CRM logic.

We also develop an M&A Pre-Signal Intelligence Agent that detects early indicators of acquisition or divestment intent across energy, mining, infrastructure, carbon, and climate-related sectors, helping clients anticipate strategic moves before transactions become public.