What we do, and what we will not

Enterprise Services

Consulting and delivery across AI strategy, implementation, governance, testing, architecture review and managed services.

How this is organised

Each page states what the engagement produces, what you receive, and what we will not do. Every one links to the corresponding part of our own operating model, which is published in full, because a method you can inspect is easier to judge than a capability you are asked to take on trust.

AI Strategy

Where AI creates value in your organisation, and where it does not.

Engagement

AI Implementation

Build and integrate, end to end.

Engagement

AI Governance

Policy, controls and audit readiness.

Engagement

AI Testing & Assurance

Independent evaluation of AI systems.

Engagement

Cloud Assessment

Workload-by-workload placement, a cost model built from your actual bill, a resilience position tested by removing things, and the licence exposure a migration changes.

Engagement

Managed Cloud

Monitoring, patching, cost management and incident response against a published SLA, run by a named engineer who knows your estate rather than a rotating queue.

Engagement

AI Readiness Assessment

A scored readiness position, a ranked shortlist of use cases marked viable or blocked with the reason, and a written baseline so any later benefit claim can be checked.

In progress

Cybersecurity Assessment

Control coverage against NIST CSF 2.0 and CIS v8.1, judged on evidence rather than on policy documents, with gaps ranked by exposure rather than by effort.

In progress

Managed Security

Detection monitoring with rules tested quarterly, measured remediation times, third-party access kept current, and a monthly evidence pack an auditor can read.

In progress

AI Automation

A high-volume repetitive process automated and then kept running, monitored on task success, human intervention rate and cost per completed task against a baseline.

In progress

Managed Infrastructure

A maintained dependency map, patching with evidence it ran, capacity against an evidenced peak, and a backup that has actually been restored.

In progress

AI Operations

Monitoring on the metrics that predict AI failure rather than the ones that are easy to chart: task success, intervention rate and cost per completed task.

In progress

AI Agent Management

Guardrail review, authority drift detection and injection testing for agents that act rather than answer, with a monthly report an auditor could read.

In progress

Data & Analytics Management

Quality gates that block publication rather than raise a ticket, one authoritative definition per concept, and lineage that answers a challenged number.

In progress