Instant summaries across every variable

See what you have before someone builds a dashboard.

Upload research data and see every variable—distributions, categories, and response patterns—in an explore-ready chart. AddMaple infers text, single- and multi-category, opinion-scale, numeric, and date columns on import.

Start with the structures the study actually contains.

Multi-selects, Likert grids, weights, and multi-wave trackers surface as research-native structures rather than flat spreadsheet columns. Numeric variables are binned, categorical variables show frequency counts, and text columns open word clouds.

Turn orientation into a better next question.

Expand a variable to pivot it against others, inspect related columns, or move into deeper analysis. The first view helps researchers spot data-quality issues and decide which cuts deserve banners, drivers, or qualitative coding.

Give every analyst the same first view.

Instant summaries are useful because they make the initial orientation repeatable. Instead of beginning with whichever table someone happened to request, the team can see the shape of the dataset, notice unusual distributions, and choose the next analytical question from the evidence in front of them.