The Reality Most Teams Discover Too Late
1. It Struggles in Large Spaces
Corridors stretch. Floors merge. Geometry drifts. The algorithm tolerates some inaccuracy, so errors accumulate over large spaces that chain data capture points.
2. It Doesn’t Scale
Since there is a 2,000-scan limit per tour, multiple models are required for large sites, which significantly increases hosting costs.
3. Measurements Can Be Misleading
You’re not measuring true point cloud data—you’re measuring a visual approximation. Significant errors occur if the object is too large, too small, or too shiny.
4. Your Data is NOT Yours
According to the terms and conditions, any data processed by Matterport is OWNED by Matterport. Your access—and your model—can disappear.