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Users Explorer provides a real-time, searchable view of users interacting with your AI application. It helps developers and product teams understand user-level engagement, inspect recent interactions, and analyze how individual users experience the AI agent.

Default view

The Users Explorer displays a list of users with key engagement and interaction attributes, including:
  • User ID – the unique identifier of the user
  • Last Seen – the timestamp of the user’s most recent interaction
  • Last Intent – the intent detected in the user’s most recent interaction with the AI
  • Last Sentiment – the sentiment associated with the user’s most recent interaction
  • Conversation Count – the total number of conversations the user has had with the AI agent
The list is updated automatically as new interactions occur, ensuring up-to-date visibility into user activity.

Customizing displayed attributes

You can tailor the Users Explorer table to show only the user attributes relevant to your analysis.
  • Click Configure Display (top right) to select or deselect user traits
  • Add or remove any tracked user traits from the table columns
  • Changes apply instantly, allowing flexible exploration without modifying tracking configuration
This enables teams to adapt the view for debugging, customer support, or deeper behavioral analysis.

Searching users

Use the Search field to quickly find specific users based on any tracked user trait.
  • Search by User ID, name, or any other user attribute being tracked
  • Search operates across all available user traits, not just visible columns
  • Useful for locating individual users, validating identity mapping, or investigating specific cases

Drilling into user profiles

Clicking a user opens the User Profile, where you can:
  • View the complete set of user traits and metadata
  • See a chronological list of all events and interactions generated by the user
  • Analyze the user’s full interaction history across sessions and conversations

Common use cases

  • Monitoring user engagement and activity at the individual level
  • Investigating user-specific issues or anomalies
  • Validating user traits and identity resolution
  • Supporting customer success and debugging workflows