Using AI Summaries in Views

Last updated: March 14, 2026

AI Summaries let you skip manual row-by-row analysis and get a written breakdown of your View data in seconds — including written insights, auto-generated charts, trend analysis, and actionable recommendations.

Before You Begin

  • Open any saved View with at least one result.

  • AI Summaries are available to all users at no additional cost.

  • Results are based on the object type, filters, columns, and records currently visible in the View — adjusting these will change the insights generated.

Step 1: Enable AI Analysis When Creating a View

To use AI Summaries, the View must have AI analysis enabled at creation time:

  1. Go to Views and click Create View.

  2. Enter a name, select the Object Type, and toggle on OnRamp AI Analysis.

  3. Choose which capabilities to enable:

    • Visual Data — charts and graphs that highlight patterns in your dataset

    • AI Insights — written analysis, key findings, and recommendations

  4. Click Create View.

Step 2: Generate an AI Summary

  1. Open the View you want to analyze and confirm it has results.

  2. Click Generate AI Summary in the View toolbar.

  3. Wait a moment while OnRamp AI processes your data (typically under 10 seconds).

  4. Review the output — you’ll get written insights, visualizations, trend analysis, and recommendations.

  5. If your dataset changes, click Regenerate AI Summary to refresh.

What an AI Summary Includes

  • Visual Data — charts and graphs surfacing patterns (e.g. tasks with the most comments, project status distribution, engagement trends)

  • AI Insights — written findings such as tasks that generate frequent questions, playbooks with higher engagement, or onboarding patterns worth addressing

  • Recommendations — actionable suggestions based on the dataset

Exporting AI Summaries

You can export View data and summaries for reporting or sharing with stakeholders:

  • Export Data (CSV) — exports the raw dataset used in the View

  • Export Summary (PDF) — exports the AI-generated analysis

Tips & Troubleshooting

  • Results vary: Summaries are non-deterministic — regenerating may surface new or different insights.

  • Use focused filters before generating summaries for more targeted analysis. For example, filter to customer task comments from the last 30 days to surface common friction points.

  • Summary doesn’t look right? Try regenerating, compare with your raw data, and apply your own operational knowledge.

  • Always validate AI output before making business decisions — AI can miss context your team has.

  • Consistently off? Reach out to OnRamp Support if summaries don’t align with your data.