Outcome-Focused Services
We prioritise business outcomes first, then align technology choices to your context.
Modernise Legacy Data Platforms
Challenge: Legacy estates, duplicated pipelines, and inconsistent data definitions.
Timeline: 4-9 months
Outcome: Lower delivery risk, improved data trust, and faster analytics enablement.
- 30-40% reduction in pipeline rework
- 20-30% faster analytics delivery cycles
- 2-4 priority domains stabilised in first phase
Sectors: Banking, Insurance, Property
Stack: Azure Data Platform, Databricks, SQL, governance tooling
Deliver Trusted Executive Reporting
Challenge: Slow monthly reporting, reconciliation effort, and inconsistent KPI definitions.
Timeline: 3-6 months
Outcome: Faster close-to-report cycles and higher confidence in board-level reporting.
- 25-35% faster close-to-report cycle
- 40% less manual reconciliation effort
- 1 board pack replacing 3-5 fragmented reports
Sectors: Financial Services, Property
Stack: Data modelling, semantic layers, Power BI
Build Scalable Data Foundations
Challenge: Fragmented source systems and limited enterprise analytics reuse.
Timeline: 4-8 months
Outcome: Reusable data products and stronger cross-team alignment on trusted metrics.
- 30% improvement in data reuse across teams
- 20-25% fewer metric-definition disputes
- 3+ reusable data products launched per programme
Sectors: Financial Services, Property
Stack: Modern data platforms, lakehouse patterns, data quality controls
Move AI From Experimentation To Production
Challenge: Pilot fatigue, weak governance, and unclear business value from AI initiatives.
Timeline: 3-7 months
Outcome: Production-ready AI use cases with measurable business impact and controls.
- 1-2 AI use cases moved to governed production
- 20-30% reduction in manual review effort
- 8-12 week pilot-to-production pathway
Sectors: Banking, Insurance
Stack: AI orchestration, model operations, responsible AI practices
