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Case Study 05Aspire · Data & AI
Data Foundation for Applied AI
A product organisation needed trusted data pipelines and governance before scaling AI-assisted workflows beyond experimentation.
Data EngineeringGovernanceBIGenAI Enablement
ETLWarehousePower BIRAGMLOps
1 source
Trusted reporting layer
3 use cases
Moved past pilots
Full audit
Ownership + controls
The challenge
AI experiments were outpacing data quality, ownership and controls, creating risk and limiting confidence in production use.
Our approach
- Built a governed data foundation with clear stewards and quality checks.
- Selected AI use cases with accountable owners and measurable outcomes.
- Defined monitoring, access and escalation paths before wider rollout.
Results
- Reporting and AI workflows shared a trusted data layer.
- Priority use cases moved from experimentation into operating use.
- Risk, ownership and model controls were visible to business and technology leaders.
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