Real-Time Context for Snowflake Intelligence with Confluent

This post details how Confluent Intelligence, built on Kafka and Flink, delivers real-time context to Snowflake Cortex AI agents. It introduces Confluent's Streaming Agents and Real-Time Context Engine as solutions for context engineering, enabling AI systems to operate on current, trustworthy data. The post outlines three integration patterns: using Tableflow to convert Kafka topics to Iceberg tables in Snowflake, building event-driven Streaming Agents on Confluent Cloud for reasoning and action, and leveraging the Real-Time Context Engine to serve enriched data via MCP to Cortex agents. It highlights the architectural shift towards event-driven pipelines as the application itself and contrasts this with less effective approaches like batch pipelines or direct API calls.