Global AI Impact Commons
Fetosense: AI-assisted fetal monitoring for early risk detection in low-resource maternal healthcare settings
India
Healthcare
Implementing Organisation
CareNX Innovations Private Limited
India, Maharashtra, Mumbai / Navi Mumbai
Implementing Point of Contact
Aditya Kulkarni
Founder and CEO
Contributor of the Impact Story
Carnegie India
Year of implementation
2019
Problem statement
In many rural and resource-constrained healthcare systems, access to specialized fetal monitoring and expert cardiotocography (CTG) interpretation is limited due to shortages of trained obstetricians and inadequate infrastructure. This gap often leads to delayed detection of fetal distress, preventable complications, unnecessary referrals, and avoidable Unnecessary Neonatal Intensive Care Unit (NICU) admissions, contributing to higher maternal and neonatal morbidity and mortality. Fetosense addresses this challenge by enabling point-of-care fetal monitoring with AI-assisted interpretation that reduces dependence on specialist clinicians. By supporting frontline health workers and general physicians with actionable insights, the solution improves early risk identification, referral decision-making, and continuity of care. This approach strengthens maternal health services in underserved settings while improving efficiency and equity within the healthcare system.
Impact story details
CareNX Innovations Private Limited is a healthcare technology company focused on improving maternal and fetal health outcomes in low-resource and underserved settings. Incubated at IIT Bombay and supported by national and international partners including UNICEF Venture Fund, MIT Solve, and Microsoft Founders Hub, CareNX develops clinically validated, scalable medical technologies for use in public and private healthcare systems. CareNX’s flagship solution, Fetosense, is a portable, telemetric cardiotocography (CTG) system designed to enable early identification of fetal distress during pregnancy and labor. The platform integrates affordable hardware with decision-support software and AI-assisted analytics to support frontline health workers and general physicians, especially in regions with limited access to obstetric specialists. The organization has deployed its solutions across India and other low- and middle-income countries, working with government health departments, medical colleges, district hospitals, and private healthcare providers. CareNX solutions have been used to screen over 500,000 pregnancies, contributing to improved referral decisions, reduced unnecessary NICU admissions, and better maternal-fetal outcomes. CareNX is committed to responsible and context-appropriate AI adoption. Its current AI roadmap focuses on open-source, explainable models, clinical validation, and regulatory compliance to ensure trust, safety, and scalability within national health systems.
AI Technology Used
Key Outcomes
Access
Reach, Inclusion
Equity, Accuracy
Quality Improvement, Resilience
Risk Reduction, Efficiency
Productivity
Narrative Outcome
Fetosense provides AI-assisted fetal monitoring and CTG interpretation at the point of care, extending specialist-level diagnostic capability to rural and semi-urban settings where trained obstetricians are scarce. The platform has screened hundreds of thousands of pregnancies. Participating facilities have seen NICU admissions drop by nearly a third, as clinicians can now identify fetal distress accurately without relying on precautionary referrals. The result is better-targeted interventions and reduced strain on higher-level facilities.
Impact Metrics
Total number of pregnancies screened using Fetosense
Baseline Value
There has traditionally been limited access to expert cardiotocography (CTG) in rural facilities Number of pregnant beneficiaries
Post-Implementation
More than 500,000 pregnancies across rural and semi-urban areas have been screened using the Fetosense Number of pregnant beneficiaries
Rate of Reduction in Avoidable or Unnecessary Neonatal Intensive Care
Baseline Value
Traditionally, there is a high rate of precautionary referrals made to the NICU due to the lack of interpretation support amongst clinicians Traditionally, there is a high rate of precautionary referrals made to the NICU due to the lack of interpretation support amongst clinicians Post-implementation: The use of Fetosense has led to more than a 30% reduction in NICU admissions across participating facilities Unit: Percentage
Post-Implementation
The use of Fetosense has led to more than a 30% reduction in NICU admissions across participating facilities Traditionally, there is a high rate of precautionary referrals made to the NICU due to the lack of interpretation support amongst clinicians Post-implementation: The use of Fetosense has led to more than a 30% reduction in NICU admissions across participating facilities Unit: Percentage
Implementation Context
States in India including Maharashtra, Gujarat, Rajasthan, Madhya Pradesh, Assam, and Bihar, with pilots and deployments in select Low and Middle Income Countries (LMICs) in South Asia and Africa
Pregnant women, particularly in rural, semi-urban, and underserved communities, frontline health workers, general physicians
Key Partnerships
Government health departments at the State and District level, medical colleges and public hospitals, the UNICEF Venture Fund, private hospitals and maternity clinics, and academic and research institutions
Replicability & Adaptation
1. The solution can be adapted to different geographies by localizing clinical protocols, language interfaces, referral thresholds, and data governance frameworks. 2. Open-source AI components enable customization for regional health system needs.
Supporting Materials
* The data presented is self-reported by the respective organisations. Readers should consult the original sources for further details.