Mia Spencer

Mia Spencer

  • Mia Spencer at the Airestate booth at NAR NXT, Texas
    Airestate booth, NAR NXT
    Texas
  • Mia Spencer at the Airestate booth at the New York Real Estate Expo
    Airestate booth, NYC Expo
    New York
  • NYC Real Estate Expo
    New York
  • Airestate mini-websites for real estate agents at the Southeast Real Estate Expo, Greenville
    Southeast Real Estate Expo, Greenville
    Airestate's mini-websites for agents
  • Mia Spencer with Ryan Serhant at the New York Real Estate Expo
    With Ryan Serhant
    New York Real Estate Expo
  • Mia Spencer at the South Florida Real Estate Summit, Miami
    CRE Miami
    South Florida Real Estate Summit
  • Technical strategy session with the Airestate dev team
    Tech Strategy, Bali
    With the dev team

Airestate

During travel, my friend and I kept running into the same problem: every time we moved to a new country, finding a new place was frustrating. The user experience was broken, and real estate systems were a mess.

So together with Martin, a UI/UX designer , we started Airestate . We fixed messy listing data and developed advanced clustering and a native-app experience on the web.

An Airestate listing on a phoneAn Airestate agent's page on a phone

Cloud-Native GIS

I fell in love with maps from the beginning, so I always got excited and gave my best hours to create each map.

Early on, I made tutorials to help my friends in mapping class. Then some researchers came across my channel and requested maps for their projects.

And the next thing I knew, more people kept coming. That's how Im.Carto began.

We've now created more than 1,000 maps, working with researchers, mapping consultants and governments.

Somewhere along the way, I kept thinking about my mission in cartography.

Even early on, I felt something was missing when mapping in GIS apps. They're heavy, and I couldn't work from anywhere.

Besides that, most of my time went into preparing the data: cleaning it and converting rasters to vectors. Some parts of mapping are also quite repetitive, like weighting, overlays and scoring. Yes, ModelBuilder helps with the repetitive steps.

But wait, there's more: what about finding the data? Or picking the right method from a number of studies? That takes time too.

Each of these parts can be optimized, and people have already started building pieces of this future: cloud-based solutions, autonomous workflows, MCP and more.

CARTOWherobotsFelt

Imagine all of it coming together. Think of how many hours we'd save with faster decision-making and autonomous geoprocessing workflows.

That's where I'm going.
I hope to meet cartographers with the same mission along the way!