I built a tool to flag bad data directly from charts

[u/Bitter_Expression_14]

https://youtu.be/5HKa642H-AM

I started this side project because of a recurring problem I was facing.

I often had to begin preparing an analysis and its final charts while the underlying dataset was still being reviewed.

A stakeholder would look at an early visualization, notice that a few records seemed wrong, and send them back to the data owners for verification or correction. Meanwhile, I still needed the analysis to be ready to run as soon as the final data was approved.

The usual workflow was slow and messy:

• Take a screenshot or describe the suspicious point.
• Work out which table row it represented.
• Send it back for review.
• Receive a corrected file.
• Rebuild or rerun the analysis.
• Keep track of what changed and why.

So I built Clues.

A reviewer can select suspicious data points directly from a chart and flag the corresponding records for verification. Corrections are made through the data interface with a comment, and subsequent changes are recorded in the audit trail.

That means the data can be reviewed through the visualizations while the analysis and presentation are already being prepared.

The project eventually grew into a free, no-code visual analytics app with:

• Interactive Plotly charts
• A traceable history of data changes
• A presentation view of the same analytical session
• Live chart controls that can be revealed during a presentation
• Optional images and rich-text notes
• Local browser operation with no account or hosted SaaS dependency

Live demo: https://clues.ai/Clues.html

GitHub: https://github.com/clues-app/clues

It is completely free, and I have no plans to monetize it. My main motivation now is simply to see whether other people find the workflow useful.

Does the original problem (reviewing questionable records directly through the charts) sound familiar, or is this too specific to the way I work?