Built on 25 years of operational modelling.

International Data Flows is the company behind Cortex.

The company was born from operational modelling work in Scotland’s energy sector and has spent more than 25 years helping complex organisations understand how people, processes, systems, data, infrastructure and dependencies connect.

That experience shaped a clear belief: organisations make better decisions when they can see how they actually work.

Cortex applies that modelling discipline to AI operational governance. It helps organisations understand where AI-enabled activity sits, what it touches, who remains accountable and what evidence is available for review.

Why we exist

Operational context, made clearer.

Modern organisations are increasingly dependent on systems, data, automation and AI-enabled activity. But many still lack a clear view of how those dependencies work in practice.

Critical data may move through teams, applications, platforms, infrastructure, suppliers and decision points before it reaches the people or processes that rely on it. Over time, systems change, documentation falls behind and institutional knowledge becomes fragmented.

In those conditions, governance becomes harder. Risk is harder to assess. Assurance becomes more dependent on interpretation. Change can create consequences that were not visible at the point of decision.

International Data Flows exists to make operational context clearer.

Cortex continues that work for organisations introducing AI-enabled activity into real operational environments.

Our modelling heritage

Built around dependency.

For more than two decades, International Data Flows has developed and applied a proprietary operational modelling approach for understanding how organisations, systems, connectivity and data flows depend on one another.

The approach focuses on the relationships between people, processes, applications, systems, infrastructure and the data that flows through them. It is designed to create a shared operational picture that technical and non-technical stakeholders can use together.

That shared picture helps organisations reveal dependencies, validate assumptions, identify points of fragility, expose legacy constraints and support better decisions about governance, resilience, transformation and risk.

The principle is simple: organisations cannot govern what they cannot clearly see.

Proven across complex operational environments

Shaped where consequence matters.

The company’s modelling discipline has been shaped in environments where clarity, accountability and operational consequence matter.

That includes public-sector, regulated, energy, aviation, nuclear, policing, financial, education and critical-service environments.

Each environment is different, but the pattern is consistent. Complex organisations need a clearer view of how work is actually supported by systems, data, infrastructure, suppliers and decision processes.

When that context is unclear, assumptions begin to replace evidence. When it is visible, organisations can reason more clearly about change, risk, accountability and value.

Cortex carries that discipline forward into the governance of AI-enabled activity.

From operational modelling to AI governance

AI governance cannot rely on policy alone.

As AI-enabled activity moves into operational use, organisations need to understand the context around it: what it can access, what it may affect, which systems and data it depends on, where boundaries sit and who remains accountable.

Cortex is designed around that need.

It connects AI operational governance to the organisation itself. Rather than treating AI as an isolated technology choice, Cortex helps frame AI-enabled activity in relation to real processes, systems, data flows, dependencies and evidence.

That is the bridge between International Data Flows’ modelling heritage and Cortex’s role today.

Operational context makes governance practical. Evidence makes review possible. Accountability keeps responsibility visible.

How we think

Start with the organisation, not the model.

We believe AI governance should start with the organisation, not the model. The most important questions are often practical ones:

Where is AI-enabled activity being introduced? What operational context surrounds it? What systems, data and dependencies does it touch? What evidence is available for review? Who remains accountable when decisions, recommendations or actions are influenced by AI?

Cortex is built around those questions. Our approach is guided by four principles:

Context before claims.

AI governance needs to be grounded in how the organisation actually works.

Evidence before assurance.

Review depends on traceable evidence, not statements of intent alone.

Accountability before automation.

AI-enabled activity should not obscure who remains responsible for outcomes.

Modelling before scale.

Organisations should understand operational dependency before expanding AI use.

This is the company view behind Cortex: governed AI operations begin with clear operational context.

If that view resonates with a challenge your organisation is working through, start a conversation.