Arcane.Engine

Arcane.Engine was born from a reflection on accounting. Two experienced professionals can analyse the same situation and reach different interpretations, not necessarily because they do not know the rules, but because they draw on distinct experiences, criteria and contextual knowledge.

Information systems can record operations, organise data and automate many tasks. But an important part of specialist work still depends on the human ability to interpret circumstances, recognise exceptions and assess alternatives.

Arcane.Engine’s initial hypothesis was to explore to what extent that reasoning could be observed, structured and represented computationally, making it possible to preserve and share knowledge that often remains implicit.

The project’s evolution brought a new question: to support a specialist’s reasoning, it is not enough to know the rules and the criteria they use. It is also necessary to understand the reality in which they operate.

It was from this reflection that Argus.Context emerged, conceived as a layer of Arcane.Engine dedicated to observing external events potentially relevant to each organisation.

A regulatory change, an economic shift or an event affecting a supplier can have very different consequences depending on each company’s reality. Information on its own does not make those consequences understandable. It has to be related to the organisation’s specific context.

This evolution widened Arcane.Engine’s ambition: from a reflection on specialist reasoning to a broader investigation into the relationship between knowledge, context, learning and organisational decision-making.

Arcane.Engine does not seek to find a universally correct answer to every problem. In business decisions, there are often alternatives with different risks, benefits and consequences.

The project explores the possibility of making those alternatives more understandable, identifying the assumptions, the constraints and the trade-offs associated with each path.

In this vision, technology does not replace human judgement. It seeks to extend the ability of specialists and decision-makers to understand reality, anticipate possibilities and take better-informed decisions.

Arcane.Engine remains a conceptual research project, with open scientific and technological questions.

Among them, it matters to understand to what extent professional judgement can be formalised, how to represent context adequately, how to distinguish causal relationships from mere correlations and how to allow a system to learn from the consequences of earlier decisions.

There is also a fundamental question of responsibility: how to ensure that the use of these capabilities strengthens, rather than diminishes, human understanding and control over decisions?

It is these uncertainties that guide the project’s evolution.