Data engineering, AI and intelligent automation for the enterprise.
Data engineering, analytics, machine learning, AI agents and automation, delivered as one programme and anchored in the business process they serve.
- The foundationGoverned data platformmodelled, owned and documented
- What it supportsAnalytics and BInumbers people trustApplied AIgrounded in that same data
- Where it landsThe business processwhere the decision is made
- Supported as data, models and usage change
Platform, intelligence
and reporting.
Each capability can be engaged separately or combined, depending on what a programme requires.
Snowflake
A governed data foundation. Advisory and architecture, warehouse migration and ELT modernisation, data engineering, performance and cost optimisation, access governance, and ongoing platform support.
The capabilityArtificial intelligence
Intelligence applied to a business process. Use-case assessment and readiness, machine learning, generative AI, AI agents with human oversight, intelligent automation, enterprise integration, governance, and support once live.
The reporting layerAnalytics and business intelligence
Business intelligence, data science and big data analysis. The reporting foundation that makes AI investment dependable.
Reliable data first.
Then intelligence.
AI programmes most often stall on data readiness, reporting quality or integration rather than on the model itself.
Establish the data foundation
Consolidate and govern the data first. Without lineage, quality and access control, AI output is difficult to trust or audit, however good the model.
Make reporting trustworthy
Get analytics and business intelligence right. Where reporting is not trusted today, generated answers will not be trusted either.
Prioritise use cases on evidence
Assess candidates against business value, data readiness and the cost of error. Use cases that are not yet viable are identified early.
Integrate and support
Connect intelligence to the systems of record so results reach the people doing the work, then support it as data, models and usage change.
Supporting expertise.
Data and AI engagements draw on the integration, platform and governance capabilities we already provide.
Discuss your data platform or AI requirement.
Tell us about the data you hold, the systems it lives in, and the decision you want it to support.