AI Architecture
Data, retrieval, orchestration, model access, evaluation and the controls around them, designed as one system against your constraints — latency, cost, residency, skills on the ground.
What we do
Ten capabilities. One team. No handoffs to a partner you have never met.
The architecture, the models and the governance are held by the same people. That is the whole proposition: nothing gets lost in the gap between the firm that designed it and the firm that has to make it defensible.
Capabilities
Enterprise Architecture
Where AI meets the estate you already run. Capability maps, target states and migration paths that respect the systems, contracts and people you cannot simply replace.
AI Governance & Regulatory Readiness
An operating model your own people can run: inventory, classification, stage gates, roles and evidence, mapped to the EU AI Act, ISO/IEC 42001 and NIST AI RMF.
AI Risk & Impact Assessment
Seven stages — context, people, data, model, decisions, controls, residual — ending in one of five decisions, including "do not proceed". Written so a regulator, an auditor and an engineer all read the same thing.
Model Training & Fine-tuning
Task-specific models trained, fine-tuned and evaluated against a baseline you agreed in advance — with the honest answer about when a smaller model, or no model, wins.
Data Engineering & Dataset Build
The unglamorous half of every AI programme: pipelines, lineage, labelling, quality gates and a dataset that is documented well enough for someone else to defend it.
Applied Research
A question your team does not have the weeks to answer: does this approach work on our data, at our scale, within our constraints. Run properly, written up, reproducible.
Statistical Modelling & Analysis
Forecasting, causal questions, experiment design and the uncertainty published alongside the estimate. The baseline that stops an expensive model being bought for a problem regression already solves.
Agentic Automation
Where an agent genuinely removes work, and where it just moves the risk. Tooling, state, routing, escalation paths and the human checkpoints that keep it accountable.
Fractional AI Architect
Senior architecture authority on retainer. Decisions made and recorded, reviews attended, governance kept running in the months between programmes.
Seven ways to start.
Each one is fixed in scope and ends in something written down. What one covers is on the discipline page. What it costs, and how long it takes, depend on your estate — we agree both at scoping, in writing, before we start.
01 AI Discovery & Scoping Define the problem, requirements, feasibility, options, costs and delivery approach. 02 AI Solution Design Implementation-ready enterprise AI architecture and technical design. 03 AI Architecture Review Independent assessment of an existing AI architecture. 04 Enterprise AI Platform Architecture Organisation-wide target and reference architecture with a transition roadmap. 05 AI Governance & Regulatory Readiness An AI governance framework mapped to applicable regulation and recognised standards. 06 AI Risk & Impact Assessment A structured assessment of one AI system covering risks, impacts, controls and residual risk. 07 Fractional AI Architect Ongoing architecture authority, governance and design support.
Not sure which
Not sure which one you need? That is the first conversation.
Describe the situation and we will tell you which engagement fits — including when the answer is that you do not need one.