> ## Documentation Index
> Fetch the complete documentation index at: https://docs.openlit.io/llms.txt
> Use this file to discover all available pages before exploring further.

# AI Analysis

> Turn a trace or span into a structured, AI-generated review of performance, reliability, cost, and token efficiency

Every trace and span in the [Traces detail view](/latest/openlit/observability/telemetry/traces) has an **AI Analysis** tab. Use it to turn raw OpenTelemetry data into a structured review instead of reading spans by hand.

Analysis runs at two scopes:

* **Trace hierarchy analysis** (the AI Analysis tab in the left-hand view-mode row): reviews the root span and every child span together, so you can understand the full request - agent path, tool calls, model calls, retries, errors, and cost drivers.
* **Individual span analysis** (the AI Analysis tab in the right-hand attributes panel): focuses on the single span currently selected, for when you need to inspect one model call, tool execution, retrieval step, error, or latency hotspot.

## Analysis dimensions

Each run is broken into dimension tabs:

* **Strengths**: what the trace did well - efficient paths, good cache usage, appropriate model choice.
* **Improvements**: concrete, actionable changes, each with a severity, an explanation, and a suggested fix shown as a word-diff preview.
* **Wrong turns**: retries, repeated span names, and other signs the agent backtracked or looped.
* **Cost**: cost per call, the most expensive span, and where spend concentrates.
* **Token efficiency**: input/output/cache/reasoning token usage, duplicate tool or retrieval inputs, and repeated context.
* **Path**: the request's execution path across services, tools, databases, and HTTP calls.

## Run analysis from trace details

1. Open a trace from the Traces page or from a trace widget.
2. Select the **AI Analysis** tab - in the left panel for the whole trace, or in the right panel for the currently selected span.
3. Click **Analyze**. Progress streams in as the analysis runs.
4. When the run completes, it's saved to a run history tab so you can revisit it without re-running. Use **Re-run** only when the trace data or your investigation question has changed.

Each finding card includes a **Try in Chat** button that hands the finding off to Otter with context pre-filled, so you can keep investigating conversationally instead of staying in the panel.

## Run analysis from Otter

You can also ask [Otter](/latest/openlit/chat/overview) to analyze traces or spans by natural language - Otter has dedicated tools for running or retrieving AI Analysis runs, including by session, user, or any custom span attribute:

```
"Analyze this trace hierarchy"
"Review span <span_id> for token waste"
"Find cost optimization opportunities for traces where session.id is dc7b1ba1-..."
"Analyze the slowest traces from the last 24 hours"
```

When Otter references a trace or span in its answer, OpenLIT renders clickable trace/span pills so you can jump back into the trace detail view.

***

<CardGroup cols={2}>
  <Card title="Traces & Exceptions" href="/latest/openlit/observability/telemetry/traces" icon="diagram-project">
    Where the AI Analysis tab lives inside the trace detail view
  </Card>

  <Card title="Chat with Otter" href="/latest/openlit/chat/conversations" icon="comment">
    Ask Otter to run analysis, find traces, or explain findings in natural language
  </Card>
</CardGroup>