Beta · in testing

Charts that don't mislead.

FairCharts reviews any chart, flags what's misleading or unclear, and hands back a corrected version, with the reasoning. Built on decades of visualization research.

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Same data. One version earns trust, the other loses it.

Not every distortion is in the axis. Some are in what gets left out. Each fix is tied to a named principle, so you can defend the chart in the room, not just make it prettier. The charts below are our own reconstructions on illustrative numbers.

● Before

Quarterly revenue ($M)

Quarterly revenue ($M) FY26 · axis starts at 90 90 92 94 96 98 92 94 96 98 Q1 Q2 Q3 Q4 Illustrative data
● After

Quarterly revenue ($M)

Quarterly revenue ($M) FY26 · axis starts at 0 0 25 50 75 100 92 94 96 98 Q1 Q2 Q3 Q4 Illustrative data
The flaw · distorting encoding
The y-axis started at 90, not 0. On a bar chart, length is the value, so a clipped baseline turns a 6-point rise into a towering one. Start bars at zero and the real story shows: steady, modest growth.
● Before

Revenue growth by product line

JanFebMarAprMayJun100150200250300Indexed (Jan = 100)ABCRevenue growth by product line (indexed, Jan = 100)Illustrative data
● After

ARR by product line ($K, actual)

JanJunJanJunJanJun$0$1,000$2,000$3,000$4,000A · $4.00M → $3.70M ▼$0$500$1,000$1,500B · $1.20M → $1.52M ▲$0$50$100$150$200C · $0.08M → $0.24M ▲ARR by product line ($K, actual)Illustrative data · each panel on its own zero-based $K axis
The flaw · misrepresents the data
Indexing every line to 100 hides the dollars. Product A is by far the biggest, and it is the one actually shrinking ($4.0M → $3.7M), a bigger loss than C’s celebrated “300” is a gain. Show the real ARR and you see which way the money is moving.
1

Drop in your chart

Upload an image, or paste your data table for a fix that uses your real numbers.

2

See what's wrong

Issues ranked by how misleading they are, each tied to a named visualization principle.

3

Get the fixed version

A corrected, presentation-ready chart you can drop straight into the deck, with the reasoning to back it.

A misleading chart in front of a client costs more than an ugly one.

FairCharts is built for consultants and analysts whose charts carry their credibility. Catch the truncated axis, the wrong chart type, the unreadable palette, before your client does.

What people ask about honest charts.

What is FairCharts?

FairCharts is a tool, currently in beta, that reviews a chart, flags what's misleading or unclear, and returns a corrected version with the reasoning. It uses established data-visualization principles to judge what's wrong, then hands back a presentation-ready fix you can defend.

What makes a chart misleading?

A chart misleads when its visual encoding doesn't match the numbers, or when the data shown is selected to flatter a story. Common cases: a truncated axis on a bar chart, a chart type that can't answer the question being asked, two independent y-axes forced into lockstep, and a cropped time range that hides the fuller trend.

When is a pie chart the wrong choice?

A pie chart is the wrong choice when the task is to rank or compare similar values, because the eye judges angle and area poorly. When you need to see which is biggest, sorted bars on a common scale read at a glance where a pie can't.

Is FairCharts available yet?

FairCharts is in pre-launch beta. The public site is a preview with a waitlist; join it to be notified when the beta opens. It's provided free and as-is while we test. See the terms for what that means.

Who's behind FairCharts?

FairCharts is built by Sergej Stoppel, Ph.D. in visualization and intelligent interaction systems, with over a decade building production AI systems for large enterprises. The critique draws on decades of established visualization research, and every fix is tied to a named visualization principle, not a matter of taste.

Be first to put your charts on trial.

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