Confluent's Real-Time Context Engine, available in Early Access, aims to streamline the process of integrating real-time data into production AI systems by leveraging Apache Kafka and Apache Flink. This innovation addresses the challenges of mapping disparate data models, maintaining governance, and rebuilding pipelines due to schema changes by unifying streaming data into a single managed service. It continuously materializes enriched data sets into a fast in-memory cache and serves them using the Model Context Protocol (MCP), abstracting the complexities of Kafka and Flink. This approach contrasts with traditional methods that either focus solely on real-time data access or contextual richness, offering a comprehensive solution that combines both. The engine forms part of Confluent Intelligence's broader vision to harness real-time data for AI, enabling secure, scalable, and efficient data integration and processing for intelligent systems directly on the Confluent platform.