AI for health supply chains.
Offline first intelligence for improving health commodity availability in low resource humanitarian settings.
Presenting the AI framework for health supply chains to sector stakeholdersStrengthening supply decisions where infrastructure is constrained.
Neuravox Foundation is developing AI systems that help health teams make better supply chain decisions in settings where internet connectivity, infrastructure, storage capacity, and reporting systems are unreliable.
The work combines field evidence, offline first system design, human in the loop governance, and applied forecasting methods to support better stock visibility and commodity availability. It began with an AI framework for health supply chain optimization in Uganda and is now advancing toward tool development for forecasting, stock visibility, and decision support.
AI must work with the constraints on the ground.
Health facilities in humanitarian and low resource settings often operate with unreliable connectivity, fragmented reporting workflows, limited storage capacity, and recurring stockouts. AI systems designed for these environments must treat intermittent internet, incomplete data, and mixed paper and digital workflows as the operating baseline.
What the field evidence shows.
A 2024 needs assessment and a 2025 baseline assessment across pilot facilities in Karamoja and South Western Uganda established the operating reality the system is designed for.
89%
Unreliable connectivity
of assessed facilities operate with unreliable internet and power.
100%
Experienced stockouts
of pilot facilities recorded stockouts of essential commodities.
120 days
Longest stockout
maximum stockout duration recorded at refugee serving facilities.
r = −0.695
Storage vs. stockouts
storage capacity showed a strong negative correlation with stockout burden.
In response, the framework uses an offline first, human in the loop, infrastructure aware approach designed to augment existing paper and digital workflows.
From framework to working tools.
The project is moving from framework development into tool development. The next phase focuses on supply optimization tools that can support facility level decisions offline, consolidate district level forecasts, and give national teams better visibility into risk, demand, and infrastructure constraints.
Forecasting
Demand forecasting that works with incomplete data and treats storage and budget as hard constraints.
Stock visibility
Facility, district, and national views of stock, risk, and infrastructure constraints that survive intermittent connectivity.
Decision support
Recommendations health workers can accept, adjust, or reject, keeping decision authority with people.
Reporting
Paper and digital outputs that match existing registers so the system fits current workflows.
The framework is the foundation phase.
The AI framework defines the technical, operational, and ethical foundation for the tool. It includes offline workflows, a forecasting architecture, integration standards, fraud prevention mechanisms, decision making protocols, and humanitarian AI safeguards.
The framework builds on earlier humanitarian innovation research conducted in Uganda with support from the UK Foreign, Commonwealth & Development Office and the Elrha Humanitarian Innovation Fund. It is now maintained by Neuravox Foundation as the institutional home for this work.
Translating the framework into usable software.
The tool development phase will translate the framework into usable software components for forecasting, stock visibility, decision support, and reporting. The design preserves human decision making authority and fits into existing health system workflows.
This is a framework to tool development pathway. The tools are in active development and have not been deployed at scale; the pilot evidence and framework define how they are being designed and validated.
Continuity of leadership.
HIF supported framework and baseline work in Uganda, led by Gideon Abako, with IFRAD serving as local grant host.
Neuravox Foundation serves as the institutional home for tool development, implementation, and scale up.
Built to support people and protect accountability.
The system must remain human in the loop, auditable, privacy aware, and infrastructure aware. It supports health workers and decision makers. Final judgement stays with them.
Human in the loop
AI advises and health workers decide. Overrides are treated as expertise.
Auditable
Every recommendation and adjustment is explainable and recorded for accountability.
Privacy aware
Encrypted local storage and data minimisation, aligned with Uganda's Data Protection and Privacy Act (2019).
Infrastructure aware
Designed for constrained power, storage, and connectivity.
Dig into the technical detail.
Strengthen health supply chains with us.
We work with funders, ministries, humanitarian agencies, and technical collaborators advancing supply chain resilience in low resource settings.