Analytics, Data Infrastructure and AI Reporting Support

Kantoko required support to strengthen its analytics and reporting capability as its healthcare operations continued to grow. The organisation needed clearer visibility across operational and clinical workflows, more reliable reporting foundations, and the ability to explore AI-assisted analysis for internal use cases.

Key challenges included:

• Limited visibility across operational and clinical performance measures
• Manual or fragmented reporting processes that made routine analysis inefficient
• A need for business intelligence dashboards to support clinical governance and operational oversight
• Data infrastructure that required uplift to support scalable reporting and future AI integration
• Emerging requirements for semantic analysis and ad-hoc AI-assisted reporting

We supported Kantoko across analytics, data infrastructure, and applied AI reporting initiatives, with a focus on practical implementation and long-term maintainability.

Solution components:

• Analytics & Business Intelligence: Designed and developed Metabase dashboards to improve visibility across operational efficiency, service delivery, and clinical governance measures
• Dashboard Development: Built reporting views and dashboard components to support internal monitoring, decision-making, and recurring management reporting
• Data Infrastructure Uplift: Improved the data environment using Databricks, dbt, and Spark to provide a stronger foundation for reporting, analytics, and AI integration
• Data Modelling & Transformation: Developed structured data models and transformation workflows to improve consistency, reliability, and usability of reporting data
• Ad-hoc AI Solutions: Delivered targeted AI-assisted solutions for semantic analysis, reporting support, and internal data exploration
• Service Support & Enablement: Worked with Kantoko's team to ensure dashboards, data workflows, and AI outputs were practical, understandable, and aligned to operational needs

The work helped Kantoko improve internal reporting capability, strengthen its data foundations, and explore applied AI use cases in a controlled, service-oriented manner.

Business impact:

• Improved operational visibility through Metabase dashboards covering operational and clinical workflows
• Strengthened reporting foundations with Databricks, dbt, and Spark-based modelling and transformation workflows
• Supported clinical governance and management reporting with more consistent business intelligence views
• Established AI-assisted analysis patterns for semantic analysis, reporting support, and internal data exploration
• Improved data readiness for future analytics and AI integration work