The missing data link in enterprise AI: Why agents need streaming context, not just better prompts
Enterprise AI agents today face a fundamental timing problem: They can't easily act on critical business events because they aren't always aware of them in real-time.The challenge is infrastructure. Most enterprise data lives in databases fed by extract-transform-load (ETL) jobs that run hourly or daily — ultimately too slow for agents that must respond in real time.One potential way to tackle that challenge is to have agents directly interface with streaming data systems. Among the primary approaches in use today are the open source Apache Kafka and Apache Flink technologies. There are multiple commercial implementations based on those technologies, too, Confluent, which is led by the original creators behind Kafka, being one of them.Today, Confluent is introducing a real-time [...]
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