For AI agents: A markdown version of this page is available at https://docs.datadoghq.com/real_user_monitoring/ai_investigations/multi_view_ai_investigation.md. A documentation index is available at /llms.txt.

Multi-View AI Investigation

Join the Preview!

Multi-View AI Investigation is in Preview.

Request Access

Overview

Multi-View AI Investigation runs an agentic root-cause analysis across a sample of views that share a slow performance vital. While Single-View AI Investigation explains why one view was slow, Multi-View AI Investigation explains why an entire (view × vital) pair is consistently slow across users. Use it from the Optimization page when you have identified a specific page and vital and want to know what to fix first.

The investigation runs at the (view × vital) granularity and is available for the following vitals:

  • Loading Time
  • Largest Contentful Paint
  • First Contentful Paint
  • Interaction to Next Paint

Prerequisites

Multi-View AI Investigation is available for Browser RUM applications only.

Launch an investigation

  1. Open the Optimization page for your application.
  2. Select a view and one of the supported vitals.
  3. The Optimization page surfaces two elements for the selected (view × vital) pair:
    • A summary at the top with an at-a-glance overview of the issues detected.
    • Up to three recommendation cards below the summary. Each card represents a candidate root cause, ordered by impact.
  4. Click Investigate on a card to launch the agent on that issue.
Optimization page for a Largest Contentful Paint metric, showing the p75 distribution, time series, and ranked recommendation cards with an Investigate button on each card.

What the agent investigates

The agent groups its findings into four diagnostic types:

SourceWhat is examined
Resource bottleneckSlow resources (HTML, scripts, images) impacting the vital across views.
Vital elementDOM elements that contribute most to the Largest Contentful Paint (LCP) or Interaction to Next Paint (INP) score for the view.
Top JavaScript filesLarge JavaScript bundles or packages that dominate execution time.
Long tasksLong-running tasks that block the main thread during the vital window.

The richer the data available, the more precise the analysis. Correlating RUM with APM Traces and enabling Browser profiling helps the agent attribute findings to specific code paths.

Read the results

When you click Investigate on a recommendation card, a side panel opens and the agent streams its analysis in real time. Each investigation produces:

  • A step-by-step timeline describing how the metric is built from your application code: which resources load, when scripts execute, and where time is spent during the vital window.
  • A root-cause explanation with the supporting evidence the agent considered.
  • A code-level finding when the agent can attribute the issue to a specific file or function.
A Code Investigation side panel showing the inspected DOM element, a timeline of layout and render events, the root-cause explanation, and the affected source code.

Take action

After an investigation completes, you can act on findings without leaving the panel:

  • Fix with Bits: Opens the Bits AI dev assistant with the investigation context pre-filled to generate a code fix from your IDE.
  • Save to a Notebook: Exports the full timeline and findings to a Notebook to share with your team.

Further reading

Additional helpful documentation, links, and articles:

AI InvestigationsDOCUMENTATION more more Single-View AI InvestigationDOCUMENTATION more more Optimize page performance with RUMDOCUMENTATION more more