Introducing Mappt: maps without the data wrangling
If you've ever tried to put data on a map, you know the shape of the problem. You start with a clear idea — show me sales by zip code, show me incidents on a heatmap, show me where my customers are. Two hours later you're still renaming columns, hunting for matching GeoJSON, fighting projections, or pasting CSV rows into a tool that wants something slightly different than what you have.
The actual map — the part that creates value — takes a few clicks. It was never the bottleneck.
Creating maps is fun. Preparing data is not.
That gap is what Mappt is built to close. The pitch is simple: bring whatever data you have, in whatever shape it's in, and Mappt turns it into a real, interactive map. No reformatting. No geocoding scripts. No lookups against a shapefile you found on page three of a government portal.
You have three ways to start:
- Paste a URL. A public dataset, an open data portal, a CSV someone shared — Mappt pulls it in and figures out the geometry.
- Upload a file. CSV, Excel, GeoJSON, KML, or Shapefile. Messy column names are fine; unusual projections are fine.
- Describe what you want. "Population density by US county" or "EV charging stations in Berlin" — Mappt sources the data and builds the layer for you.
What you can build today
Mappt isn't a styled basemap with pins. It's a real analysis surface. From day one you can:
- Stack layers — points, lines, polygons, choropleths, heatmaps, 3D bars — on the same map.
- Pin widgets to layers: histograms, pie charts, and bar charts that update as you pan and zoom.
- Run spatial operations — joins, filters, intersections — without leaving the map.
- Export the map as a PNG, or export individual layers back out to CSV, KML, or Shapefile.
- Share an interactive view with a link. The recipient gets the live map, not a screenshot.
Why we built it this way
We came at this from two sides. One of us spent years working with spatial data and watched smart people repeatedly hit the same wall: the tools assume you've already done the hard part. The other half of the team has been building AI-first products and saw exactly where a model could carry the load — schema inference, geocoding, format translation, the long tail of small judgment calls that usually fall on the analyst.
So Mappt is opinionated about one thing: the time between "I have this data" and "I'm looking at a map" should be measured in seconds, not afternoons.
What's next
We're building in the open. Expect more layer types, deeper spatial analysis, and tighter integrations with the places your data already lives. If there's something you wish a map tool could do — tell us. We read every message.
In the meantime, the fastest way to see what Mappt is about is to try it on your own data. It takes about a minute.