Enterprise AI agent observability with BigQuery and Looker
As enterprises move AI agents from experimental prototypes into production, data and platform teams are discovering that deploying an agent is only half the battle — you also need to see how it reasons, which data it touches, and what it costs to run. Today, we are announcing expanded AI agent observability and evaluation capabilities across Google Data Cloud, giving you unified visibility into your first-party (1P) data agents in BigQuery and Looker as well as custom third-party (3P) agents built with agent development frameworks such as Agent Development Kit (ADK) or LangGraph.
Putting conversational and autonomous agents into production requires solving three operational challenges: tracing multi-step reasoning while protecting sensitive data, controlling token consumption and query spend, and evaluating answer accuracy before prompt or schema changes reach users. Let’s explore how our new agent observability and evaluation capabilities help you do this.
What's new: Agent observability across Data Cloud
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