From mothers, community health providers, clinicians, donors, NGO partners, and government stakeholders.
Maternanet helps the health system identify pregnant women who are at high risk of complications weeks before those complications occur. We do this by giving community health providers digital tools to screen mothers at home, running that data through a predictive risk model, and sending an automatic alert when a mother's risk profile crosses a threshold. The CHP then makes a priority visit or coordinates a timely clinic appointment before an emergency develops.
Think of it as a smoke detector for maternal health — except instead of detecting a fire already burning, it detects the conditions that make a fire likely. We also help remove the financial barrier to acting on that alert through our Care Now, Lipa Later microfinancing partnership.
Our Composite Women's Health Index™ synthesizes 85 variables across three categories:
Validated against clinical outcomes and WHO checklist-based scoring. Recall (sensitivity): 79% — 21pp better than standard care. Precision: 81% — providers are not overwhelmed by false alerts.
Critically, the model explains its reasoning. A provider sees which specific indicators are driving the score, enabling clinical confidence rather than blind algorithmic compliance.
This is by design, not an afterthought. 60% of our users access via SMS or USSD on feature phones with no data connection.
Patent filed: "Distributed Healthcare ML with Progressive Sync" — Kenya Patent Office, Application #2024/789.
No. Maternanet operates on a strict human-in-the-loop principle. Our model only flags and recommends — it never decides or acts autonomously. Every alert generates a human action: a CHP visit, a clinical escalation, a facility appointment. The clinician always makes the final call.
In a context where Africa faces a shortage of 6.1 million healthcare workers, our goal is to make every CHP significantly more effective — helping them prioritise their caseloads intelligently and focus their limited time on the mothers who need them most.
Maternanet operates on a Two-Channel Architecture to integrate natively with Kenya's national DHIS2 system and EMRs while securing direct depth data:
Setup: 2–4 weeks including staff training. One-time $399 fee + $85/month facility licence. Contact info@maternanet.com for a free trial.
Across 4 active Kenyan counties (Nairobi, Narok, Machakos, Kajiado) over 18 months of deployment:
Validation: ANC data cross-referenced against county DHIS2 records and independent clinic registers. Our quasi-experimental evaluation uses difference-in-differences methodology with matched comparison sites and continuous model improvement. A peer-reviewed paper is in preparation with a Kenyan university partner for Year 3–5 validation.
Currently $8,100 per life saved, projected to fall to $650–$1,300 by 2028 as scale increases. The WHO estimates skilled birth attendance programmes cost $4,000–$12,000 per maternal death prevented — our model is competitive now and improves dramatically with volume.
Early intervention also reduces average care costs by up to 70% by treating complications early rather than managing emergencies.
Yes — and this is the clinical foundation of Maternanet. Machine learning risk models for pre-eclampsia and obstetric complications have been validated in peer-reviewed literature (BioMed Central, WHO Digital Guidelines) showing clinically useful discrimination using routine maternal data. Risk profile simulation for prenatal risk monitoring is an emerging but evidence-supported methodology.
Our model identifies the combination of signals that, in aggregate, indicate elevated risk weeks before clinical symptoms manifest — giving CHPs and clinicians a window for intervention that standard screening misses entirely.
A Digital Doula is an existing community health provider (CHP) equipped by Maternanet to conduct community-level screenings, follow up on flagged high-risk mothers, and bridge the household-to-clinic gap where most maternal deaths happen.
Currently 410 active Digital Doulas across 4 counties, with a 96% retention rate.
Most digital health interventions fail here. We built Maternanet from within the communities we serve — our founding team comes from these regions and understands that trust is earned through presence, not technology.
Our 77% weekly engagement and retention rate — in communities with historically low digital health adoption — is the evidence this approach works.
Detecting risk without removing the barrier to acting on it is not a solution; fortunately we realized this earlier on. Maternanet addresses the financial barrier through two mechanisms:
Our B2B revenue model subsidises care at the community level. The mother pays nothing extra. We take from the institutional top of the pyramid and give to the bottom.
Integration follows a four-step pathway:
Pricing: $85/month facility licence + $399 one-time setup. Revenue-sharing partnerships available. Contact info@maternanet.com.
Three primary partnership models:
Early-mover partners in Uganda, Tanzania, Rwanda, Nigeria, and Ghana receive preferential data access and co-authorship opportunities on evidence outputs. Contact info@maternanet.com.
Currently deploying a $550,000 strategic capital round (through Q1 2027) to build the data foundation that unlocks high-margin DaaS revenue streams at scale by 2028–2029:
Trajectory: $95,897 actual 2025 revenue → $536,303 projected 2029. EBITDA break-even Q4 2026. ROI visible 18–25 months post-deployment. Contact owinoaketch@maternanet.com for the full investor pack.
No. Three diversified, reinforcing revenue streams:
Grants and impact investment accelerate deployment — they do not sustain it. 20%+ net margins projected by 2028. Commercial success and social impact grow in the same direction: more enrolled mothers → better model → lower cost per outcome.
ODPC registration and DPIA approval in progress. KMPDC telehealth certification expected Q3 2026.
Whether our predictive tools qualify as Software as a Medical Device (SaMD) under Kenya PPB and WHO frameworks is a question we are actively working through — proactively, not reactively.
Current regulatory status:
Long-term vision: 1M+ women across 5 countries, Kenya achieving fewer than 150 maternal deaths per 100,000 live births by 2030.
Our model is transferable wherever three conditions exist: a community health worker structure, 2G mobile coverage (minimum), and a maternal mortality challenge driven by detection delays and access barriers. That describes most of sub-Saharan Africa.
Deployment requirements:
We are actively seeking early-mover partners in Uganda, Tanzania, Rwanda, Nigeria, and Ghana. Contact info@maternanet.com with your context.
Maternanet is built to demonstrate SDG 3 achievement through a replicable, cost-effective model — not just aspire to it.
Primary alignment: SDG 3 (Good Health and Well-being), SDG 5 (Gender Equality), SDG 10 (Reduced Inequalities)
Secondary alignment: SDG 1 (No Poverty — reduced catastrophic healthcare costs), SDG 8 (Decent Work — CHP jobs), SDG 9 (Innovation and Infrastructure), SDG 17 (Partnerships)
We respond to every message within 48 hours — and yes, a human reads every email.