Case studies
A selection of delivery work across regulated environments, designed for repeatability, auditability and clear stakeholder value.
Filters below highlight the main theme of each piece.
All
NLP & ML
Automation
Cloud
Governance
Large-scale NLP
Conversation analytics at operational scale
Delivered an automated pipeline to analyse 800k+ digital customer interactions, including robust text preparation,
classification and keyword/theme outputs. Produced stakeholder-ready dashboards with consistent definitions and traceable metrics.
Regulatory automation
From month-end reporting to daily delivery
Reworked a high-volume reporting workflow using Python-based quality controls and statistical checks.
Reduced publication timelines from weeks to hours while improving repeatability and providing clear exception handling.
ML prioritisation
Risk and issue signals for programme planning
Applied NLP techniques to structured and unstructured RAID-style data to support prioritisation across complex programmes.
Focused on explainable features and clear communication of uncertainty to decision-makers.
Cloud pipelines
Lakehouse patterns for repeatable analytics
Built production-grade ingestion and transformation workflows with strong operational controls:
lineage, scheduled execution, data quality assertions and clear ownership boundaries between teams.
Secure delivery
Analytics platforms that work for the whole organisation
Designed secure internal tooling and dashboards serving large user groups, with governance-friendly access patterns,
resilient scheduling and clear documentation to support operational handover.
Real-time BI
Automated insight delivery for high-visibility moments
Implemented automated reporting pipelines feeding live dashboards. Designed for low manual effort, predictable refresh behaviour,
and rapid interpretation by non-technical stakeholders.