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Outputs

Generative Charts

Turn natural language or data into editable visualizations inside the answer. People get charts they can tweak, not only prose about numbers.

Interactive demo

Overview

How might we design generative charts so people can trust and act on AI output?

When to use

  • Perfect for analytics tools, business intelligence platforms, and data exploration applications where generating charts from natural language makes data visualization accessible.

When to skip

  • Questions that need a single number, not a chart.
  • Datasets too large to render faithfully in-chat.
  • Compliance views that require certified BI tools instead of chat charts.

Rules

  • Charts with no access to underlying data.

  • Misleading scales or truncated axes without notice.

  • Non-editable images when the product could offer a real chart object.

  • Inventing data points not present in sources.

Evidence

ProductImplementation
JuliusChat-driven chart generation from datasets.
TableauAsk Data style NL to visualization.
Power BICopilot-assisted visual creation.
Google SheetsAI-assisted chart suggestions from ranges.

FAQ

What makes generative charts trustworthy?

Linked source data, labeled axes, and the ability to open or download the series, not a decorative PNG.

Should users be able to edit the chart?

Yes: chart type, filters, and fields. Treat the first render as a draft.

How does this relate to generative UI?

Gen charts are a specialized GenUI component focused on visualization.

When to refuse a chart?

When data is missing, sparse, or the request would mislead. Explain and offer a table instead.