Strategy and feasibility
Assessing use cases, sharpening problem definitions, testing expected value and determining whether AI really is the right approach.
Consultancy
We help organisations determine where AI and automation genuinely add value, and what needs to be in order first to arrive at a solution that works in practice.
First the problem, then the technology.
Many AI initiatives start with a model, platform or architecture and then look for a problem to match. That leads to expensive experiments, solutions that are hard to control and results that look convincing but deliver little value.
We start from the question that needs to be solved. Then we assess the quality of the data, the existing processes, the risks, the technical feasibility and the expected added value.
That is essential, because AI does not only amplify what is right. It also scales up poor data, flawed processes and biases into professional-looking results that can be worthless in substance.
The outcome therefore does not necessarily have to be an AI solution. Classic automation, better data, a search solution or a simpler deterministic process can be a better fit.
From a critical review of an early idea to architecture, governance and technical guidance during delivery.
Assessing use cases, sharpening problem definitions, testing expected value and determining whether AI really is the right approach.
Technical designs for AI, data and automation that fit existing platforms, security and operational management.
Defining roles, decision-making, quality controls and technical measures so that solutions remain explainable, manageable and verifiable.
We help with early ideas, stalled projects, architecture choices and projects where ambition, technology and reality are no longer aligned.