Case Study: Nearmap achieves scalable, high-quality training data for geospatial AI with CloudFactory

Growing geospatial applications with quality training data

Nearmap, a global geospatial imagery company, faced the challenge of producing high-quality, large-scale labels for its AI-powered aerial image analysis while avoiding the distraction of in-house annotation work. To scale and standardize labeling across varied imagery types and proprietary tooling, Nearmap engaged CloudFactory and its Computer Vision Managed Workforce to take over the data-labeling function.

CloudFactory provided a trained, accountable labeling team, rapid onboarding, ongoing quality reviews, and integration with Nearmap’s custom tools. Over a 3+ year partnership CloudFactory has delivered 300,000+ hours of annotation, increased monthly throughput roughly 10x from an initial ~200 hours per month, improved label quality and model performance, and enabled new products like roof-geometry insights — demonstrating measurable, scalable impact for Nearmap.

Nearmap

Michael Bewley

Senior Director of AI Systems