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Use Conversation Diagnosis when you need to understand why the agent behaved a certain way on a specific turn — which functions ran, which topics were cited, and where latency occurred. Toggle data layers in the diagnosis panel to inspect each turn in detail.

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Available diagnosis views

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Conversation variables

Displays live variable values captured during the call (e.g., booking IDs, customer names, flags).

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Flows and steps

Tracks the agent’s navigation through flows and steps, showing the execution path and decisions made.

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Tool calls

View the tools the agent triggered during the call, including call parameters and outcomes. conversations-function

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Topic citations

Highlights the Knowledge topics the agent matched for each response. conversations-topics

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Sources

Shows which Connected Knowledge source files the agent retrieved for each turn. Click a source name to open an inline preview panel showing the retrieved content. Use Open in Knowledge in the panel to navigate directly to the source. sources-conversation-review

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Transcript corrections

Displays where the automatic transcript was edited for clarity or accuracy.

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Turn latency

Measures how long the agent took to respond at each turn.
Latency visualization includes detailed breakdowns to help identify performance bottlenecks.

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Latency breakdown

When viewing turn latency, you can inspect timing for:
ComponentDescription
LLM requestsTime spent waiting for the language model to generate a response
Function callsTime spent executing functions, including API calls and data processing
Total response timeCombined time from user speech end to agent response start
Use these breakdowns to:
  • Identify slow function calls that need optimization
  • Understand LLM response times for different query types
  • Find bottlenecks causing user-perceived delays
  • Compare latency across different conversation types
High LLM latency may indicate complex prompts that could be simplified. High function call latency often points to slow external API dependencies.

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Interruptions

Shows when the caller interrupted the agent or when barge-in was detected.

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Variants

Identifies which variant handled each part of the call.

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Logs

Displays function logs and any structured conv.log entries emitted during runtime.

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Entities

Lists extracted entities captured from the user, like booking numbers, account IDs, or city names. This is especially useful in transactional scenarios where the agent needs to capture structured data from free text.

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Using diagnosis for optimization

Combine multiple diagnosis views to understand agent behavior:
  1. Enable Turn latency to identify slow responses.
  2. Check Tool calls for those turns to see if external calls are causing delays.
  3. Use Sources to verify the content the agent retrieved from Connected Knowledge.
  4. Use Flows and steps to verify the agent followed the expected path.
Last modified on March 26, 2026