About us
EPCON is an impact company, using AI to help NGOs and governments in LMIC to strengthen public health, through the Epi-control platform.
Our partners use our Epi-control platform for more efficient case-finding interventions, diagnostic network optimization, treatment outcome prediction, improved vaccination planning or service delivery. From complex data to evidence based actions.
Why work with us
01
Proven
impact
Delivering measurable improvements in TB, HIV, malaria and outbreak response across 40+ countries through AI-driven decision support.
02
Built for implementation
Fast, flexible and scalable deployment designed for NGOs, Ministries of Health and frontline teams operating in complex environments
03
From prediction
to action
Transforming epidemiological intelligence into concrete operational planning through hotspot prediction, microplanning and resource optimization.
04
Trusted long-term partner
Combining advanced AI expertise with deep public health knowledge, capacity building and strong collaboration with local and global partners
"Our evidence proves that EPCON is a foundational enhancer of efficiency in public health [...] Invest in AI-driven platforms. They work because you will reach more people, optimize efficiency, and you will save more lives."
Dr. Joseph Daniel,
Program manager at
IHVN, Nigeria
What partners say about us
"[…] with the Epi-control platform, we were […] able to find over 1300 patients in one year, using about twenty community healthcare workers[…] That means that you are […] able to prevent disease or reduce the spread of disease. Public health organisations and government institutions would really benefit from this platform, because it helps them to identify which communities are at risk and which strategies are the most impactful […]."
Dr. Sipho Nyanthi,
Public Health Manager at
Aquity innovations, South Africa
Dr. Abiola Alege,
Senior Program Manager at
SFH, Nigeria
"The impact of the model goes beyond the 12000 people diagnosed with TB […] The model has helped us to divert our limited resources to areas for maximum outreach. The most amazing thing about this model is it’s interoperability. We’ve linked it to several other platforms integrate with our exisiting platforms. Beyond using it to predict for TB hotspots, we’ve also gone to use it to […] prevention of mother-to-child HIV in pregnant women and children living with HIV."
