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Infographic Options & Styles

The infographic generator gives you several settings to control how much information is shown and how the output looks.

Controls how much information the AI extracts from your documents:

LevelDescription
ConciseQuick-glance summary with a small number of key metrics and minimal annotation
StandardBalanced overview with moderate metric coverage and clearer supporting context
DetailedDeep extraction with denser metrics, richer key points, and more structured modules

The generator enforces different density contracts for each level so the visual output changes meaningfully, not just stylistically.

Determines the shape of the generated image:

OrientationBest For
LandscapeSlide decks, presentations, LinkedIn posts
PortraitInstagram Stories, mobile content, posters
SquareSocial media posts (Instagram, X/Twitter)
StyleDescription
Auto-selectThe AI picks the most appropriate style and layout family based on your content type, audience intent, and evidence shape
CorporateExecutive-ready visual language with restrained palette and clean hierarchy
ProfessionalPolished business/editorial look with balanced accents and clear structure
ScientificPrecision-first style with explicit labels and neutral, data-focused treatment
Sketch noteHand-drawn sketchnote style — informal and engaging

The generator now varies composition more deliberately inside each style. That means two infographics can both be Professional but still resolve into very different structures, such as a comparison split, a timeline ribbon, a process flow, or a trend-led hero layout, depending on the source material.

The steering prompt (up to 500 characters) is the most powerful control you have over the output. It guides both what data the AI focuses on and how the image looks:

  • “Use a dark background with gold accents” — influences the visual design.
  • “Focus on the operational efficiency section, not revenue” — directs which content is extracted.
  • “Create a comparison between Q2 and Q3 results” — shapes the content structure.

Specific structural prompts usually produce the biggest quality jump. Prompts like “Make this a before-versus-after comparison”, “Use a step-by-step process flow”, or “Lead with the strongest trend and keep the rest as supporting modules” give the planner a stronger signal than generic requests like “make it look better.”

You can optionally restrict the infographic to content from specific files in your project. This is useful when a project contains many documents but you only want the infographic to draw from one particular report.

Use these patterns to get more predictable results:

  • Keep inputs specific and scoped to one intent per generation request.
  • Save intermediate outputs often, especially before running major edits or regenerations.
  • Use review and assignment workflows early to reduce rework late in the lifecycle.

If results are not what you expected:

  • Verify source quality first (missing context, inconsistent structure, or conflicting inputs reduce output quality).
  • Re-check selected options and audience/profile settings before re-running.
  • If a job fails repeatedly, wait briefly and retry once; then escalate with the artifact or job context.

Different input context, settings, and model/runtime conditions can produce different outputs.

Regenerate when the core structure is wrong; manually edit when only wording, ordering, or style needs adjustment.

What is the best way to reduce iteration cycles?

Section titled “What is the best way to reduce iteration cycles?”

Start with clear scope, run smaller batches, and use review checkpoints after each major step.