Agentic AI represents a significant advancement over traditional chatbots by enabling systems to proactively take actions based on real-time context rather than merely responding to user inquiries. This approach involves constructing a comprehensive pipeline utilizing Java for application development, Kafka for event streaming, and DeltaStream for real-time data processing. The architecture consists of four main components: a data generator simulating an e-commerce environment to produce user events, DeltaStream to process these events into meaningful user profiles, a Model Context Protocol (MCP) server providing an API for access to these profiles, and the agentic AI that leverages this context to make informed decisions. This setup allows the AI to perform tasks like offering assistance during user struggles with checkout processes or providing discounts to encourage purchases, illustrating a shift from reactive to proactive AI systems.