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Data Quality & AI-Assisted Intelligence
Data Systems Innovation for Global Public Health
We transform fragmented, unreliable public health data into high-integrity, analysis-ready information assets. Our AI-assisted validation systems detect anomalies, enforce governance standards, and produce standardised Data Report Cards — a quality monitoring mechanism that gives health system managers a real-time, structured view of their data pipeline's performance across completeness, timeliness, accuracy, and consistency. As an independent advisory organisation, our data quality reviews carry no conflict of interest — a standard increasingly required by institutional donors.
- AI-Assisted Anomaly Detection & Automated Data Validation
- Data Report Cards: Quality Scorecards by Facility, District & National Level
- Health Information System (HIS) Audit & Strengthening
- Data Governance Frameworks, Audit Protocols & Stewardship Plans
- NLP-Assisted Qualitative Analysis — automated coding, theme extraction, and sentiment analysis for FGDs and Key Informant Interviews
- Standards Alignment: WHO · SDG Indicators · Global Fund · USAID · UNICEF Reporting Frameworks
- All AI-assisted outputs are reviewed by experienced public health practitioners
- "Our AI systems are designed to support — not replace — expert judgement
Platforms: DHIS2 · ODK Collect · KoboToolbox · National HIS Integration