Which BI tools let you measure AI response time?

Quoted from Databricks’s docsQuery system.ai_gateway.usage to analyze model requests by user, model, or workspace, including token usage, latency, and errors.

Quoted from Snowflake’s docsUse the agent-observability-report sub-skill of the CoCo agent-studio skill in the CoCo CLI to generate a report on agent monitoring metrics pulled from SNOWFLAKE.LOCAL.AI_OBSERVABILITY_EVENTS, including usage and adoption, latency percentiles, token economics, tool execution stats, conversation depth and completion, and a breakdown of user feedback.

Quoted from Omni’s docsAggregate metrics for the run include total credits, total duration, and overall accuracy, so you can summarize a run at a glance.

Quoted from Hex’s docsMeasure consistency, run time, and credit usage

Quoted from Sigma’s docsDetails about requests by model, tokens by model, average response time by model, and unique users by model.

Quoted from BigQuery’s docsAgent metrics include agent usage, model calls, tool usage, health, latency, and token usage.

Quoted from Looker’s docsLatency: The end-to-end duration, in seconds, of a single conversation turn from the moment a user submits a query to when the final response is delivered.

Quoted from Power BI’s docsThe time in seconds it took to load or query the visual