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Collection visualizations
Visualizations turn your collections into charts — distributions, trends, and comparisons — without exporting anything to a spreadsheet. Charts live in two places:
  • The Visualize tab of a collection — charts built from that collection’s data
  • The Visualizations page — all your saved charts across collections, in one dashboard

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Chart Types

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Creating a Chart

1

Open the Visualize tab

From a collection’s detail page, switch to Visualize and click New Chart.
2

Choose a chart type

Pick Bar, Line, Pie, Scatter, or Heatmap.
3

Map your columns

  • X Axis — the column to spread across (a category or a date)
  • Y Axis — the numeric column to measure
  • Group By (optional) — split the measure into series by another column
4

Pick an aggregate

Choose how values are combined: Sum, Average, Count, Min, or Max.
5

Name and create

Give the chart a title and click Create. It appears in the collection’s Visualize tab and on the global Visualizations page.
Charts compute over the entire collection, using the same exact aggregation engine agents use. A “Sum of deal_value by stage” bar chart and an agent answering “total pipeline by stage” produce the same numbers.

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Example Charts

A few combinations that work well as a starting dashboard:
  • Sales pipeline — Bar chart: sum of deal_value by stage; Bar chart: count of deals by owner
  • Customer feedback — Pie chart: count by sentiment; Line chart: average nps_score by month
  • Product catalog — Bar chart: count of products by category
  • Error logs — Line chart: error count by day; Heatmap: errors by service and severity

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Best Practices

Charts group by exact values. Normalize category columns (consistent casing and wording) before building charts, or you will see duplicate bars for the same logical category.
Sum and Average silently skip empty cells. If a numeric column has many gaps, a Count chart gives a more honest picture of your data.
Three to six charts per topic is usually enough. If a chart never changes your decisions, remove it.

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Next Steps

Working with Data

Clean your data before charting it

Using Collections with Agents

Let agents run the same aggregations conversationally