Cloudbuilder

A data platform practice. Principal-led. Built in production, handed over running.

Databricks and Azure-native delivery. Governed AI. The engagements that hold under real load and regulator scrutiny.

Where it has run

Production engagements across regulated and commercial sectors.

The practice has delivered for British Car Auctions, Castle Trust Bank, Heathrow Airport, David Lloyd Leisure, Mindshare, and Wates Construction in commercial industries. In public sector and regulated bodies: NHS Property Services, The Pensions Regulator, Royal College of Surgeons, the Charity Commission, and the MHRA.

Financial services, regulated infrastructure, high-volume marketplace analytics — the engagements that require the platform to hold under real load and regulator scrutiny.

Engagement model

Production-grade delivery. Governed by design.

The platform runs in your environment, on your data. Audit trails, deterministic replay, and lineage are built in — not bolted on. Principal-led from scope to handover.

1

Scope

A direct conversation about what you are trying to build, the data, the governance, and the constraints. Outcome: an architecture and a delivery plan that fit the environment, not a templated proposal.

2

Build

Production-grade delivery on Databricks Lakehouse and Azure-native pipelines, deployed in your environment, on your data. Quality gates and lineage from day one. Audit trails and deterministic replay built in.

3

Govern

Governance is the design contract, not a phase at the end. Every transformation traceable, every decision auditable. The platform is built to satisfy regulator scrutiny without rework.

4

Hand over

The platform runs in production, governed end to end. Documentation, monitoring, and runbooks in place. Your team takes ownership; the practice steps back.