Joining the Tech for Good journey: The DMF Chatbot and the Benefits of Data at Scale

At the DO MORE FOUNDATION, our commitment to social good is rooted in empowering communities, particularly through programmes focused on early learning and responsive caregiving. As our reach grows, so does the critical need for effective and efficient data collection. This challenge, identified by our Monitoring, Evaluation, and Learning (MEL) officer, Thea Wynne, led to the development of the DMF Chatbot which was a leap forward in harnessing artificial intelligence and big data for social good.

The Imperative for Scalable Data Collection

Our flagship Early Learning and Play-based Training (ELPT) programme has experienced remarkable growth. From initially engaging 624 caregivers through five master trainers and 21 ECD centres, it has rapidly expanded to 17 master trainers, 90 centres, and over 2,340 caregivers. This scale-up brought a clear question: how do we effectively collect data across a large, geographically dispersed network to ensure every community voice is heard and every impact accurately measured? Traditional methods, such as manual data entry or basic tools like Google Forms, began to show limitations. We needed a solution that was robust, accessible, and user-friendly, even in remote areas.

The DMF Chatbot: A Digital Bridge for Data

Our answer was the DMF Chatbot, designed to integrate seamlessly with WhatsApp — transforming it into a dedicated “DMF Chatbot Line.” This approach is driven by several key objectives:

• Data Collection at Scale: Capturing thousands of caregiver voices and measuring impact across vast areas.
• Enhanced Accessibility: Leveraging WhatsApp’s widespread use to reach remote communities and ensure inclusivity.
• Operational Efficiency: Saving an estimated one week of manpower each month, allowing our teams to focus on analysis and programming.
• Cost-Effectiveness and Scalability: A solution designed to expand easily, support multiple languages, and grow from local to global with minimal added costs.
• Immediate Insights: Enabling real-time data reporting, improved impact measurement, and evidence-based decision-making.
• Governance and Accountability: Ensuring secure data collection and transparent reporting to partners.
• User-Centric Management: Simplifying data processing and empowering our team with tools to create and adapt forms independently.
• Strategic AI and Cloud Integration: Built on a cloud foundation with AI features like anomaly detection, sentiment analysis, knowledge management, and OCR for reading documents such as attendance registers.

Principles Realised by the MEL Innovation Team

Through the DMF Chatbot, our MEL innovation team has realised core principles:

• Effective and scalable data collection.
• Increased accessibility, reaching even the most remote communities.
• Operational savings and streamlined processes.
• Affordability paired with vast scalability.
• Real-time, actionable insights.
• Strong governance and accountability.
• Simple, adaptable data management.
• Advanced AI-enabled features supporting deeper programme intelligence.

Our roadmap includes piloting WhatsApp in communities (January 2024), launching the bot with targeted forms (February 2025), and rolling out nationally (April 2025). We are mindful of anticipated challenges such as digital literacy, connectivity, and language nuances, and are proactively addressing these.

Recognition at the BRICS Youth Innovation Summit 2025

The DMF Chatbot marks a significant milestone in transforming how we understand community needs and report on our impact. It exemplifies our commitment to using technology to amplify voices and drive meaningful change.

We were proud to showcase this work at the BRICS Youth Innovation Summit 2025 in Cape Town, where the DO MORE FOUNDATION placed 2nd in the Artificial Intelligence & Big Data for Social Good category among over 600 global applications.

A heartfelt thank you to our partners at Tregter, and acknowledgement to Thea Wynne, our MEL Officer who led this innovation, and Ferdinand Steenkamp from Tregter, whose expertise helped make this vision a reality.