Learn how streaming data takes your AI from reactive to proactive with a new O'Reilly report on the foundations and real-world applications driving instant intelligence.

Redpanda

Real-time AI processes data and makes decisions with extremely low latency as events happen, rather than through batch processing. Event streaming is the optimal pattern for real-time AI because it provides persistent, replayable logs that allow AI models to learn from historical patterns while responding to current events. AI can run on-device, at the edge, or centralized in the cloud, with trade-offs between latency and computational power. Industries like financial services, cybersecurity, AdTech, manufacturing, and gaming are already leveraging real-time AI to compress the time between insight and action. Emerging applications include agentic AI for autonomous decision-making and RAG for context-aware responses without hallucinations.

Streaming data for real-time AI applications

What’s next for real-time AI (and how to get ahead) #