Agents need immediate, reliable access to live context. ClickHouse combines continuous ingestion, fast analytical queries and massive concurrency in one platform, making it perfectly suited for the demands of agentic AI.
Using the Agentic Data Stack and my Agentic Analytics Framework, I help companies build trustworthy, private and scalable AI solutions built on top of real time data foundations. This incorporates Langfuse, a ClickHouse native platform for AI governance, control and cost tracking.
Two short demos of agentic analytics running end to end on ClickHouse. Both run against self hosted open source models rather than frontier APIs, showing that trustworthy, private and cost effective agentic experiences can be built entirely on open infrastructure.
An internal analyst asks natural language questions of live ClickHouse data. The agent plans, queries and returns governed answers with the underlying SQL surfaced for review.
A consumer facing product where end users interact conversationally with their own data in ClickHouse, powered by an open source model behind the scenes.
I regularly share what I'm learning about building trustworthy, production grade agentic AI on ClickHouse from architecture patterns to hands on lessons from real client work.

As companies execute their AI strategies, most databases can't keep up with the concurrency, freshness and price/performance that agentic workloads demand. Here's why ClickHouse is uniquely well suited.

Agentic analytics is a step beyond text-to-SQL — planning, decomposition and iteration over your data. Here's what it means in practice and why ClickHouse is a natural fit.

How to combine open source and open weight models such as Deepseek, GLM and Kimi with ClickHouse using third party inference providers like Fireworks.ai and Baseten.

A walkthrough of self hosting an open source model such as GLM, connecting it to ClickHouse for agentic analytics, and the benefits around data locality, cost and privacy.

How ClickHouse have assembled ClickHouse, the ClickHouse MCP server and LibreChat into an integrated agentic data stack — and why this combination is well suited for building agentic analytics and internal agent teams.

Agentic analytics is changing how financial services firms explore data — moving beyond text-to-SQL into scenario modelling, strategy development and real partnership with the LLM. Here's why ClickHouse is the right database to build on.

A bake off of Claude and Gemini in order to test their SQL performance against a ClickHouse database.
Whether you are exploring your first agentic analytics prototype or scaling an existing deployment, get in touch to discuss how ClickHouse can sit at the centre of your AI strategy.
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