Strengthening Maternal and Child Health Outcomes in Urban Vulnerable Communities
Case at a Glance
Impact
63%
digital onboarding achieved among pregnant women (vs. 70% benchmark)
61%
of onboarded users engaged multiple times with the chatbot.
60%
of users asked two or more relevant health questions; 42% asked five or more
About the organisation
SNEHA is a nonprofit organisation committed to improving health, nutrition, and safety outcomes for women and children living in urban vulnerable communities. Working closely with communities and public systems, SNEHA designs scalable, replicable interventions that strengthen access, equity, and accountability across maternal and child health services.
Problem Statement
Women living in urban vulnerable communities face limited access to timely, accurate, and contextual health information. Barriers such as low literacy, distance from health services, and high caseloads for frontline health workers reduce opportunities for continuous guidance. As a result, critical maternal and child health practice such as early registration, institutional delivery, and timely immunisation are often delayed or missed.
Solution
SNEHA developed a GenAI-enabled WhatsApp chatbot, ‘Phonewali SNEHA Didi’, to provide women with personalised maternal and child health information. The solution delivers voice- and text-based guidance, behavioural nudges, and two-way interaction with human-in-the-loop support, ensuring privacy, contextual relevance, and 24×7 access to trusted health information.
Quick Facts
Organisation Name
SNEHA (Society for Nutrition Education & Health Action)
Organisation Website
Visit Site
Founding Year
1999
Number of Beneficiaries served
620,000+ women, children, and healthcare workers reached
Geography Served
Maharashtra- Mumbai, Thane & Palghar Dadra Nagar Haveli and Daman & Diu In other states of India, work in technical partnership with the Government, on-ground NGOs and with Foundations.
Focus Area
Programmatic Impact Capacity Development
Functions Impacted
Program Delivery / Beneficiary Services Technology & Data Management
Service Provider
Tech4Dev
Contact Email
sweety@snehamumbai.org
SDG Addressed
Full Case Study
Challenge
Limited access to reliable health information constrained preventive care
Key challenges faced by women in urban informal settlements included:
- Low literacy levels limiting the effectiveness of text-heavy health communication
- Overburdened frontline health workers with limited capacity for continuous follow-up
- Fragmented access to health information across pregnancy, birth preparedness, and early childhood
- Lack of real-time data for program teams to monitor engagement and adapt interventions
These constraints reduce timely health-seeking behaviour and weaken the effectiveness of maternal and child health programs.
Solution
A multilingual, voice-enabled AI health assistant embedded in community programs
SNEHA transitioned its chatbot from a menu-based system to a GenAI-enabled, voice-and-text WhatsApp assistant. The chatbot provides personalised nudges aligned to pregnancy stage, immunisation schedules, and child health milestones.
Key features of the solution include:
- Voice and text interface designed for low-literacy users
- Multilingual, context-sensitive responses available 24×7
- Personalised behavioural nudges across the maternal and child health journey
- Two-way chat with human-in-the-loop escalation for guidance and safety
- Dashboard-driven monitoring using DALGO–Superset for real-time insights
Outcomes & Impact
Strengthening health awareness and enabling timely care-seeking
- User engagement 970+ women engaged, with over 60% asking multiple, relevant health questions
- Behaviour reinforcement Increased early antenatal registration, institutional deliveries, and child immunisation uptake within program cohorts.
- Operational insight Real-time dashboards enabled program teams to monitor engagement and refine content continuously
Technology Stack
| Name of the Tool | Where it was used | What it enabled | Category |
|---|---|---|---|
| WhatsApp Chatbot (Glific) | Community programs | Two-way, low-barrier health communication | Open-source |
| GenAI & LLMs (OpenAI) | Health content delivery | Personalised responses and multilingual guidance | Commercial |
| NLP & LLM Fine-tuning | Chatbot logic | Contextual, health-stage-aligned nudges | Commercial |
| DALGO + Superset Dashboards | Program monitoring | Real-time analytics and engagement tracking | Open-source |
| CommCare Integration | Health worker systems | Data flow from community onboarding | Commercial |
| PostgreSQL & BigQuery | Data storage and analysis | Secure, scalable data management | Open-source |
Key Project Learnings
- Meeting Users Where They Are Enables Engagement: Delivering health guidance through WhatsApp and voice interfaces reduced literacy barriers and led to sustained interaction with the chatbot.
- Personalisation Strengthens Behaviour Change: Stage-specific nudges and contextual responses reinforced key health practices, supporting improvements in care-seeking behaviours.
- Data Feedback Improves Program Design: Real-time dashboards allowed teams to adapt content and outreach strategies, improving relevance and engagement over time.
Potential for Wider Adaption
| Sector | Adaptability of the Solution |
|---|---|
| Public Health Systems | Can integrate with government platforms for digital health outreach |
Additional Details
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