A/04
Data & cloud platforms
Modernise the data and cloud foundations that AI depends on, at a cost the business can sustain.
AI is only as good as what sits beneath it
Ambitious AI plans meet their limits in the data: where it lives, who owns it, whether anyone trusts it. Getting the foundations right is unglamorous work, and it decides whether everything built on top will hold.
Results clients have seen
- Data platform total cost of ownership reduced by 10–20% by modernising legacy warehouses to a cloud lakehouse and deploying a data quality framework.
- Self-service analytics adoption up 40–60% through a centralised data platform with sandbox environments and low-code tooling.
- Data lakes at European banks, worth around €12.5M in contract value, to meet BCBS 239.
- A real-time ad bidding platform across 25 European and Latin American markets for an automotive manufacturer.
Cost under control
Standardised DevSecOps practices, technology stacks and deployment patterns have lowered run and maintenance costs by 10–15%, and disciplined cloud financial management has improved cloud margins by around 10%.
What you can expect
A data strategy with governance and stewardship people can follow
Modernisation of legacy warehouses to a cloud lakehouse
Multi-cloud strategy and target architecture across AWS, Azure and GCP
Standardised DevSecOps practices and deployment patterns
Cloud cost governance that protects margins as usage grows