This video demonstrates how I designed and implemented an AI agent–driven chatbot architecture integrated into DigiBank’s end-to-end customer journey. The solution is built around a layered system model, where a conversational AI agent orchestrates interactions between the user interface (UI) and banking APIs, enabling secure, contextual, and task-aware assistance.

At the core, the AI agent leverages LLM orchestration and structured prompt logic to interpret user intent, maintain conversational context, and route requests to relevant backend services (such as account information, support workflows, or advisory guidance). The UX layer translates these responses into clear, human-centric interactions that simplify navigation and support real-time decision-making.

(Note: This AI case study is created for demonstration purposes to showcase how professionals can leverage AI tools for rapid conceptualization and development. When using AI tools for personal or business applications, it is essential to consider AI governance, ethical use, and regulatory compliance.)