NETALIS MEDICAL
Netalis Medical provides an offline-first, AI-assisted obstetric ultrasound solution that enables frontline healthcare workers in low-resource settings to acquire clinically usable fetal scans. The system combines portable ultrasound hardware with a proprietary 5-layer deep learning pipeline that guides probe placement, assesses image quality, and estimates gestational age—all with sub-second, on-device inference and zero cloud dependency.
- Healthcare Technology
- Medical Devices
- Artificial Intelligence
- Digital Health
- Hardware
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
More than 700 women die daily from preventable pregnancy complications, and while portable ultrasound hardware is increasingly accessible, specialist sonographer expertise is scarce—fewer than 25,800 imaging professionals serve 47 African countries. This leaves frontline nurses without the training needed to capture diagnostic imagery, resulting in millions of women in Sub-Saharan Africa going through pregnancy without a single ultrasound scan.
Solution
Netalis Medical provides an offline-first, AI-assisted obstetric ultrasound solution that combines intelligent software with portable ultrasound hardware to enable frontline healthcare workers to acquire clinically usable fetal scans. The system transforms conventional ultrasound equipment into guided imaging systems through real-time spatial UI that directs clinicians to target anatomical landmarks. A proprietary 5-layer deep learning pipeline detects fetal anatomical planes, assesses image quality in real-time, automatically captures images that meet quality criteria, estimates gestational age, and flags suspected abnormalities for clinical review. All inference runs on-device with sub-second latency and zero cloud dependency, ensuring functionality in connectivity-constrained environments. The output is conservative, assistive decision-support designed strictly for triage, referral, and regulatory trust, with final clinical decisions remaining with healthcare professionals.
Target Audience
Primary customers are public health systems, frontline primary healthcare clinics, district and provincial health services, and NGO-supported maternal programs in low-resource, connectivity-constrained regions across the Global South. The company also partners with government bodies and research institutions through structured clinical evaluation pilots.
Features
- Real-time probe guidance and fetal anatomical-plane detection (Head/BPD, Abdomen/AC, Femur/FL) via a 5-layer neural architecture
- Image-quality assessment with automatic capture when anatomical views meet system quality criteria (Good, Acceptable, Poor)
- Gestational age estimation across approximately 12–40 weeks using eight clinical developmental milestones
- Risk flagging outputting an assistive clinical risk profile (Low, Moderate, High) for frontline triage workflows
- Fully offline edge inference with sub-second latency and zero cloud dependency, optimized for low-power clinical hardware
- Deployable on standard portable ultrasound probes and clinical tablets for rapid frontline rollout without specialized infrastructure