Over 1 million women and children die or have their health compromised
from non-optimal cardiotocography* monitoring
during labour and delivery annually
Making fetal heart monitoring interpretable
Our system gives obstetric teams instant, explainable risk assessments at every CTG — so the right intervention happens before it's too late.
This is what obstetric teams navigate — every single shift
Central fetal monitoring stations display multiple simultaneous CTG traces — often more than any single clinician can actively interpret at once — with no prioritisation, no explainability, and no system-level guidance on where clinical attention is needed most.
Composite illustration — does not represent any specific vendor's product.
A global systems failure hiding in plain sight
Suboptimal CTG interpretation is not a rich-world problem. It simultaneously drives unnecessary surgery in high-income settings and preventable death in low-resource ones — while burning out the workforce asked to carry it all.
"Alarm fatigue forces labour ward nurses to re-triage their attention hundreds of times a day. Each interruption takes an average of 23 minutes to recover from — time that does not exist when sixteen lives are on the monitors."
Designed for one-to-one care. Deployed across an entire ward.
Central fetal monitoring was designed for a single bedside clinician. Today it powers entire labour wards — with no prioritisation, no hierarchy, and no intelligence to guide where attention is needed most.
No explainability.
No guidance.
Sources: JCHM 2025 · WHO 2019 · Hope for HIE 2025
The financial signal matches the clinical one
Estimated annual global economic losses from birth asphyxia and HIE in the highest-burden countries
Frontiers in Public Health, 2025Babies developing hypoxic-ischaemic encephalopathy globally every year
96% born in low- and middle-income countries. Incidence of neonatal encephalopathy is 8–16× higher in low-income settings than in high-income ones.
Frontiers in Public Health 2025 · Hope for HIE 2025Built for the people who need it most
From the labour ward to the lecture theatre to the device lab — our system adapts to how you work.
Real-time fetal risk assessment for nurses and midwives. Continuous CTG signals are processed into explainable, role-matched alerts — so your team can prioritise, escalate, and act with confidence across every bed simultaneously.
How it works →Access annotated CTG datasets paired with ground-truth umbilical cord pH outcomes. Our explainability framework helps students and residents understand the exact signal features driving each fetal risk decision — building clinical intuition alongside AI literacy.
Get in touchEmbed AI-powered CTG interpretation directly into your device software. Our API delivers real-time fetal risk scores with full decision explainability — compatible with any FHR and TOCO input stream, on-device or cloud-connected.
Partner with us
Navo Health in the news
Recognition from the innovation and healthcare community.
Interested in clinical collaboration, partnerships, or investment?
We're building with clinical institutions, OEM partners, and investors who share our mission.
Book a MeetingFrom raw CTG signal to explainable clinical decision
A neural network ingests multiple signal streams, identifies risk, and delivers role-matched output — with every decision attributed back to the signal features that drove it.
Even the best published AI models barely outperform a clinician
A Google study (2025) benchmarked multiple CTG model configurations for fetal pH prediction. Their strongest model achieved AUC 0.69 with sensitivity 0.44 at 90% specificity. Navo's model achieves AUROC 0.821 — a step change.
Avg of acidotic class sens 0.552 and normal class sens 0.389 from one-vs-rest ROC curves on held-out test set at 90% specificity operating point.