By bringing Langfuse in-house, ClickHouse can offer customers a native way to collect, store, and analyze large volumes of LLM telemetry alongside operational and business data, helping teams debug models faster, control costs, and run more reliable AI workloads without relying on a separate observability tool, Tyagi added.
ClickHouse is responding to where generative AI is “truly stuck” for enterprises, said Greyhound Research chief analyst Sanchit Vir Gogia. “Most companies are not failing to build AI features, rather they’re failing to explain them, trust them, or afford them. Models drift, costs spike, and business users can’t tell if decisions are defensible. ClickHouse is going after that precise blind spot,” Gogia said.
“With Langfuse in-house, it now has the tooling to convert every LLM call into a structured, queryable record,” Gogia noted.
