Case Studies
Enterprise Data & AI Case Studies
Real outcomes from organizations that modernized their data foundations, standardized decision‑making, and built AI‑ready architectures. Each story reflects founder‑led delivery, operational rigor, and measurable impact.
Healthcare
AI Strategy & Transformation Roadmap
From fragmented analytics to an enterprise AI operating model.
- 40% reduction in redundant analytics work
- 12‑month AI roadmap adopted
- AI use cases funded across 3 BUs
Challenge: Leadership lacked a unified AI strategy and teams were making inconsistent decisions.
Approach: Built an AI roadmap, governance model, and scalable predictive architecture.
Outcome: Redundant analytics reduced by 40% and AI use cases prioritized.
Financial Services
Enterprise Data Strategy
Building a unified data foundation for C‑suite decision‑making.
- 30% faster reporting cycles
- Standardized KPIs enterprise‑wide
- Governance framework adopted
Challenge: Leadership lacked visibility into performance drivers.
Approach: Defined KPI framework, governance, and unified data models.
Outcome: Reporting accelerated by 30% with consistent metrics.
Life Sciences
Data Warehouse Modernization
Modernizing legacy infrastructure for scale, speed, and compliance.
- 60% faster processing
- Audit‑ready lineage
- FDA‑aligned architecture
Challenge: Legacy SQL Server environment couldn’t support growth or compliance.
Approach: Modernized architecture using Fabric/Synapse patterns.
Outcome: Processing improved 60% with audit‑ready lineage.
Insurance
Dashboards & Visualization
Transforming operational reporting into executive intelligence.
- 50% reduction in manual reporting
- Real‑time visibility
- Standardized metrics
Challenge: Teams were drowning in spreadsheets with no real‑time visibility.
Approach: Built executive dashboards and semantic models.
Outcome: Manual reporting cut in half with real‑time insights.
Ready to build your own transformation story?
If you see your organization in any of these case studies, we should talk. We’ll map a clear path to an AI‑ready, enterprise‑grade data foundation.
All case studies are anonymized to protect client confidentiality while preserving the scale, complexity, and outcomes of the work delivered.