Autonomous real-time agents: the category AI has been waiting for

Autonomous real-time AI agents differ from prompt-driven assistants by continuously monitoring live business events, using current context and event-based triggers to make and execute decisions within seconds. Such capabilities could address time-sensitive problems in fraud prevention, e-commerce, logistics, manufacturing, cybersecurity, and other sectors, but have been difficult to build because they require complex streaming infrastructure for processing events, maintaining state, handling delayed data, and detecting absent events. DeltaStream positions its managed platform as a way to reduce this complexity by allowing coding agents to create streaming SQL pipelines, live contextual views, triggers, and agent workflows through an MCP interface, without requiring users to operate infrastructure or become streaming specialists. The company illustrates the approach with Double Agent, a system built in hours that detects discrepancies between AI tool requests and resulting actions, then contains and investigates suspicious activity. DeltaStream argues that lowering development time from weeks or months to hours could make real-time autonomous agents more accessible and encourage organizations to identify business moments where rapid automated action has significant value.

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