You can use Kubit to track and inspect AI agent execution paths directly inside your cloud data warehouse. It labels individual execution spans and visualizes runs as Sankey diagrams to reveal loops, errors, and drop-off points. You can group sessions into cohorts or funnels to identify recurring failure patterns and find the code changes or attributes that caused them. Kubit connects agent traces directly with business outcomes and user activity in Databricks, Snowflake, BigQuery, or ClickHouse without requiring custom SDKs or external data pipelines.
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