Agentic AI systems need a data backend that can answer high cardinality, ad-hoc analytical questions in milliseconds. This paper explains why ClickHouse has emerged as a natural fit for the data layer beneath LLM agents, and how to architect agentic applications that query, learn from and act on real-time analytical data at scale.
I have published a number of blog posts covering real time analytics, observability and AI agent scenarios for capital markets use cases. Visit the links below to learn more.