> ## Documentation Index
> Fetch the complete documentation index at: https://arizeai-433a7140.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Sessions

> Track and analyze multi-turn conversations

<Frame caption="Track multi-turn conversations with a chatbot or assistant using sessions">
  <video src="https://storage.googleapis.com/arize-phoenix-assets/assets/videos/sessions.mp4" width="100%" height="100%" style={{ display: 'block', objectFit: 'fill', backgroundColor: 'transparent' }} controls autoPlay muted loop />
</Frame>

Sessions enable tracking and organizing related traces across multi-turn conversations with your AI application. When building conversational AI, maintaining context between interactions is critical - Sessions make this possible from an observability perspective.

With Sessions in Phoenix, you can:

* Track the entire history of a conversation in a single thread

* View conversations in a chatbot-like UI showing inputs and outputs of each turn

* Search through sessions to find specific interactions

* Track token usage and latency per conversation

This feature is particularly valuable for applications where context builds over time, like chatbots, virtual assistants, or any other multi-turn interaction. By tagging spans with a consistent session ID, you create a connected view that reveals how your application performs across an entire user journey.

## Next Steps

<CardGroup cols={2}>
  <Card title="Setup Sessions" icon="gear" href="/docs/phoenix/tracing/how-to-tracing/setup-tracing/setup-sessions">
    Configure session tracking in your application
  </Card>

  <Card title="Setup Projects" icon="folder" href="/docs/phoenix/tracing/how-to-tracing/setup-tracing/setup-projects">
    Organize traces into separate projects
  </Card>
</CardGroup>