The question is, “How can large language models and mobile-first design transform the way organizations engage their audiences?” At JPMorganChase, I had the opportunity to explore this question by leading a high-impact initiative in partnership with Mothers Against Drunk Driving (MADD). With a team of seven engineers, we created a scalable platform that would not only educate but also empower users through intelligent interaction. We developed a cross-platform application designed to maximize accessibility and engagement. We used React Native for rapid front-end deployment, paired with a Python-based conversational AI layer powered by OpenAI’s models. The assistant offered a natural language interface that turned static learning into interactive conversations. Knowledge acquisition was incentivized, rewarding users for participation while making the process engaging and memorable. This architecture improved accessibility by over 55%, ensuring users could interact fluidly across devices and contexts.
The results were significant. The platform catalyzed double-digit growth in active users, proving the business viability of conversational AI in regulated enterprise environments. The success of the project earned recognition from JPMorganChase leadership, and I was honored with a formal software engineering offer as a result.