GIMS

Understand the World. Model Its Evolution. Build Scenarios.

We live in a deeply interconnected world: A regional conflict can reshape energy markets within hours. A political decision can alter global capital flows. A technological breakthrough can transform entire industries. A disruption in global supply chains can generate consequences thousands of kilometres away.

These events do not occur in isolation. They form part of a dynamic system in which decisions, interests, constraints and disturbances continuously interact.

GIMS was created to model that system.

What is GIMS?

GIMS (Geopolitical Intelligence Modelling System) is a strategic intelligence platform designed to represent and analyse the evolution of interconnected geopolitical, economic, technological and financial systems.

Its purpose is not to guess what will happen tomorrow.

The fundamental question is different: How can the World State evolve when a new Perturbation occurs?

GIMS represents the current state of the system, identifies relevant causal relationships and analyses how a perturbation may propagate through them.

From that propagation, multiple Trajectories emerge. Their convergence allows GIMS to construct probabilistic Scenarios.

Scenario probability is not assigned in advance. It emerges from the set of trajectories converging toward each scenario.

A New Approach to Complex Systems

Most financial and geopolitical analytical tools focus on observable information: prices, news, indicators, statistics or market sentiment.

These tools are extremely valuable for observing what is happening.

GIMS addresses an additional question: What structure of relationships is producing what we observe?

Markets do not exist in isolation. They are part of a broader system in which politics, geopolitics, economics, technology, resources, infrastructure, demographics and history interact continuously.

GIMS seeks to represent these interactions within a unified modelling framework.

From Event to Scenario

A Perturbation does not necessarily produce a single consequence.

It may activate several causal relationships simultaneously. Some trajectories may diverge, while others may later converge toward similar configurations.

GIMS analyses this process through a structured sequence:

World State → Perturbation → Propagation → Trajectories → Attractors → Scenarios

Attractors represent regions of trajectory space toward which different possible evolutions may converge.

Scenarios are the aggregated result of those convergences.

GIMS therefore does not need to determine in advance which scenario is most likely. Its probabilistic structure emerges from the inference process itself.

Causality as Structure

Every significant perturbation can generate a chain of consequences.

A conflict may affect energy supply.

Energy supply may alter prices.

Prices may affect inflation.

Inflation may change interest-rate expectations.

Interest rates may affect credit, consumption and investment.

Those consequences may, in turn, feed back into the system.

GIMS does not treat these relationships as a simple linear sequence of events. It represents them as a dynamic propagation structure in which relationships can diverge, converge, amplify and generate feedback.

An Interdisciplinary Framework

Reality is not organised into separate academic disciplines.

History influences politics.

Politics shapes economics.

Economics transforms international relations.

Technology changes the balance of power.

Resources constrain national strategies.

Markets respond to all of them.

GIMS therefore integrates knowledge from multiple domains, including:

• History.

• Geopolitics.

• International Relations.

• Economics and Macroeconomics.

• Finance.

• Technology.

• Strategic Studies.

• Data Science.

• Artificial Intelligence.

The objective is not simply to collect information.

It is to construct a coherent representation of the relationships between its components.

Inference Before Prediction

GIMS does not seek to produce a single deterministic answer about the future.

The system begins with a World State, incorporates observed Perturbations and explores the evolutions compatible with the known relationships.

The result is a set of trajectories and scenarios with different levels of probability and confidence.

Inference precedes conclusion.

Causal structure precedes scenario construction.

Evidence precedes probability.

Methodology Before Technology

Artificial intelligence can process extraordinary volumes of information and identify patterns that conventional methods may struggle to detect.

But technology alone does not determine what should be modelled or how a causal relationship should be interpreted.

GIMS therefore places methodology first.

Before developing algorithms, interfaces or infrastructure, the project defines how the World State should be represented, how Perturbations should be described, how causal propagation should be modelled and how Trajectories and Scenarios should emerge through probabilistic inference.

Technology is the means.

The model is the foundation.

A System That Evolves With the World

The World State is not static: Relationships change, new connections emerge, others lose relevance. Initial conditions evolve and new Perturbations continuously modify the system.

GIMS is designed to evolve with that reality.

Knowledge is incorporated, relationships are reassessed and the model can be subjected to historical validation through the Historical Replay Framework (HRF).

The objective is not to build a closed system, but an architecture capable of improving as the available knowledge grows.

Our Vision

We believe that understanding financial markets requires understanding the world that shapes them.

But we also believe that understanding the world requires more than accumulating information.

It requires representing its relationships.

GIMS seeks to build a framework capable of transforming heterogeneous information into a structured representation of the World State, analysing how Perturbations may propagate through it and generating probabilistic scenarios through a defined inference process.

We do not seek to manufacture certainty about complex systems.

We seek to build a rigorous methodology for understanding how they may evolve.

GIMS

Understand the World. Model Its Evolution. Build Scenarios.