Every engagement starts at the Audit and moves outward. You can enter the sequence at any point, but nothing gets built before readiness has been assessed.
The mandatory first engagement. Four dimensions scored against a proprietary rubric, producing a readiness report and an honest outcome track.
Most AI failures are data failures wearing a model's clothes. We map what exists, what it costs to clean, and what is lawful to use.
A sequenced plan tied to budget cycles and institutional capacity, not a wish list of capabilities.
Our specialist edge. Systems that execute multi-step work against real tools and APIs, with hardcoded human checkpoints at every consequential decision.
Sprint-based delivery with scheduled client demos. At least two model options compared before a line of production code is written.
Executive and practitioner tracks. Adoption fails when the people expected to use a system were never brought into its design.
Ongoing access to a senior practitioner after handover — for model drift, vendor decisions, and the questions that surface once a system is live.
Not every problem needs a language model, and very few need an autonomous agent. The Audit decides which layer fits — this is what each one does.
Machine learning models that analyse structured data to produce classifications, forecasts, and predictions. Mature, highly accurate for well-defined problems, and strong ROI for data-rich organisations in financial services, agriculture, and tourism.
That is precisely what the Audit is for. Start a discovery conversation and we'll give you a preliminary read before anyone talks scope.
Start an AI Audit →