What is the name of your organization?
ARMMAN
What is the name of your solution?
High-risk Pregnancy Co-pilot
Provide a one-line summary or tagline for your solution.
AI-powered learning co-pilot on WhatsApp to help Frontline Health Workers in India manage high-risk pregnancies with confidence and ease
In what city, town, or region is your solution team headquartered?
Mumbai, Maharashtra, India
In what country is your solution team headquartered?
India
What type of organization is your solution team?
Nonprofit
Film your elevator pitch.
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What specific problem are you solving?
A woman dies in childbirth every 20 minutes in India, and for every maternal death, 20 more suffer lifelong complications. Over 26,000 women die annually from pregnancy-related complications. High-risk pregnancies, which make up 20–30% of all pregnancies, account for a staggering 70–80% of perinatal mortality and morbidity, including poor neonatal outcomes.
Health workers in India—especially Auxiliary Nurse-Midwives (ANMs)—are overworked, inadequately trained, and often lack the skills needed to detect and manage complications early. Systemic issues such as inadequate and low-quality training programs and limited access to ongoing support leave them ill-equipped to manage high-risk pregnancies. Their inability to act early leads to irrational, delayed, or poorly managed referrals, which overburden tertiary facilities, compromise quality of care, and contribute to preventable maternal deaths.
Existing training models fail to support their real-time, context-specific learning needs. These challenges are worsened by digital fatigue—ANMs use 6–8 different apps daily, spending over two hours on data entry, leaving little time or energy for learning.
Globally, similar training gaps exist among community health workers. Our solution directly addresses these gaps by enabling personalized, ongoing, on-demand support for health workers and making high-quality learning and decision-support accessible at scale, even in digitally saturated, resource-constrained environments.
What is your solution?
Our solution (built in collaboration with ARTPARK) is a multilingual, multimodal learning copilot for frontline health workers (FLWs) / ANMs, designed to support on-demand and continued personalized learning on high-risk pregnancy care via WhatsApp. It delivers bite-sized lessons, answers clinical queries, and provides nudges to reinforce learning—all in the user’s preferred language and format (text or audio).
The copilot functions in two modes:
Pull mode: When an eligible FLW sends a question or topic, the copilot instantly replies with a multimedia response, drawn from a clinically validated knowledge base. Each answer is followed by suggested follow-up questions or topics, based on the user’s learning history and recent interactions. If the copilot cannot answer, the query is escalated to a human expert (e.g., Medical Officer) for support.
Push mode: The copilot proactively sends nudges, including short quizzes and recommended topics, to encourage engagement, reinforce key concepts, and ensure comprehensive topic coverage over time.
Built using generative AI, the system is designed for low-bandwidth, mobile-first environments. An early version is live with 100 ANMs in Uttar Pradesh, with plans to scale across ARMMAN’s IHRPTM program, which currently supports 20,000+ government health workers in three states.
Who does your solution serve, and in what ways will the solution impact their lives?
Our solution serves Auxiliary Nurse Midwives (ANMs), a critical cadre of government frontline health workers responsible for delivering maternal and child healthcare in India’s primary health system. There are ~150,000 ANMs nationwide, each serving 3,000–5,000 people. Despite their vital role, ANMs are overworked, under-resourced, and often lack access to continuous, practical training—especially in managing high-risk pregnancies (HRPs), which account for the majority of maternal and neonatal deaths.
ARMMAN has already trained ~9,500 ANMs across three states through classroom sessions on end-to-end HRP management, with another 10,000 scheduled for training in H1 2025. However, sustaining learning gains and translating knowledge into practice remains a challenge.
The copilot will complement and extend classroom training by offering ongoing, on-demand support through WhatsApp. It delivers personalized, bite-sized lessons, answers clinical queries in real time, and nudges ANMs to reinforce learning—all in local languages and accessible formats. This reduces their digital burden while supporting practical, real-world application of care protocols.
We aim to reach 10,000+ ANMs via the copilot within 12–18 months. By improving knowledge retention and protocol compliance, the solution will help ANMs identify HRPs early, manage them effectively, and improve maternal and neonatal outcomes.
