Mappedin raises $24.5M to digitize indoor spaces for a third of the world's malls and expand into safety

Summary

Mappedin, a Waterloo, Canada-based indoor mapping platform, has raised $24.5M to expand its data infrastructure and push deeper into public safety applications.

Hongwei Liu founded the company around a deceptively simple problem: buildings change constantly, and most mapping approaches can't keep up. Outdoor maps scraped by satellite or LiDAR stay accurate for roughly five years. Indoor maps, Liu says, are good for about five days. A mall rearranges its Santa display; a store moves its entrance. The only person who knows is the one planning it in the back office. Mappedin's model is to get ahead of that change by enabling building operators to manage and publish their own floor plan data, rather than waiting for a physical scan after the fact.

Capture methods

The platform handles both high- and low-tech ingestion. Users can walk a space with an iPhone or 360-degree camera, but Liu says the more surprising method is the most common: 70,000 people have mapped buildings simply by photographing the emergency escape diagrams already mounted on walls. Mappedin then converts those images into vector data that can feed wayfinding apps, safety systems, and third-party platforms.

Scale

The company currently powers indoor wayfinding for roughly a third of the world's malls, has run navigation at the Super Bowl four consecutive years, and is deployed at LAX. Liu estimates Mappedin's products touch about a third of Americans annually, mostly without those users knowing it.

Safety expansion

The newer growth vector is K-12 schools. Mappedin has mapped thousands of U.S. schools specifically to give first responders accurate interior maps during emergencies. The company has also seen its technology deployed by the Department of Homeland Security and various fire and police departments.

Robotics

Liu is cautious about the robotics opportunity. Indoor environments are significantly more complex than roads, training data for interior spaces is scarce and often private, and autonomous navigation outdoors has taken decades to partially solve. He thinks Mappedin is building what would become the largest interior training dataset, but puts meaningful indoor robotics applications at least a couple of years out.

On data partnerships with Google and Apple, Liu says Mappedin publishes standardized data on behalf of building owners to platforms that want it, without confirming specific names given clients' sensitivity about sharing proprietary property data with large tech companies.

The $24.5M raise is the most recent disclosed funding for the company.