Built on experience, focused on delivery
Data XL is founded by engineers with deep experience in digital health, data, and software delivery across Sub-Saharan Africa, developed through years of work at the University of California, San Francisco (UCSF).
Within UCSF, the team worked on large-scale digital health and data programmes alongside ministries of health, international donors, and implementing partners. These environments demanded systems that could operate under real-world constraints: imperfect data, complex governance, and high operational stakes.
Data XL builds on that foundation as an independent engineering company. The focus is now on delivering robust data and software systems that are practical, transparent, and designed to be operated and trusted long after initial delivery.
Data XL is based in Nairobi, with additional presence in Kampala.
Digital Health Platforms
We build digital health systems that are used in day-to-day operations, not just for reporting. These platforms bring together clinical data, laboratory results, surveillance inputs, and programme indicators into a single, coherent system.
- Case-based and longitudinal health data platforms
- Registries and electronic medical record backends, including OpenMRS and custom Python-based systems
- Interoperability layers between health systems, including national client and facility registries
Software Engineering
We build backend software that sits behind dashboards, portals, and integrations. This is production software responsible for ingesting data, enforcing logic, and serving data reliably at scale.
- APIs and backend services, primarily in Python and Node.js
- Workflow engines and data processing services
- Data-centric applications with React-based user interfaces
Data Engineering
We turn fragmented and inconsistent data into datasets that can be analysed and trusted. This work starts with understanding what data actually represents in practice, not just how it is defined on paper.
- Integration of data from multiple operational systems, including large national data warehouses
- Data remediation, validation, and harmonisation across sources and time
- Structured datasets for analytics, reporting, and downstream AI or machine learning use
Cloud and DevOps Engineering
We design and operate the cloud environments where data platforms and applications actually run. The focus is on private networking, controlled access, predictable costs, and systems that can be operated long term.
- Secure cloud infrastructure and virtual networks in Azure, Amazon, and Scaleway (EU-based, GDPR compliant)
- Deployment pipelines for data and software systems, including Docker-based builds and deployments
- Monitoring, access control, and operational tooling, including alerting and chat-based monitoring
Analytics and Decision Support
We build analytical outputs that are actively used to manage programmes and organisations. The emphasis is on clarity, consistency over time, and making decisions and trade-offs explicit.
- Operational and programme dashboards
- Monitoring and evaluation reporting
- Decision-support views for managers and technical teams, including actionable reporting