Building & Construction
Building Construction AI. Visibility, Safety, and Efficiency.

Key challenges
Construction teams use AI to improve site monitoring, safety, and progress tracking. But deploying reliable models in these environments is complex:
Site variability
Conditions change daily, affecting lighting, equipment, and workflow.
Data quality
Drone imagery and sensor data often require heavy preprocessing.
Safety risk
Poor model performance can endanger workers or delay timelines.
Integration barriers
AI systems must integrate with PM tools and construction platforms.

Key trends
Construction AI is reshaping how projects are monitored, managed, and optimized:
Progress tracking
AI models assess site conditions and compare to BIM and schedules.
Safety monitoring
Vision systems identify unsafe behaviors or hazards on site.
Material management
AI tracks inventory, equipment, and resource usage
Post-build inspection
Models assess structure integrity and code compliance.

Succeed with CloudFactory
CloudFactory helps construction companies deploy AI solutions that see clearly, adapt quickly, and deliver results:
AI Consulting
We identify AI opportunities in project tracking, site safety, and materials oversight.
Data Engine
We label drone and sensor data for monitoring, segmentation, and object tracking.
Training Engine
We fine-tune models to recognize equipment, phases, and safety patterns.
Inference Engine
We monitor live predictions for safety compliance and operational drift.
AI Engine
We bring AI into construction workflows—improving project outcomes from the ground up.
Why you need quality data labeling in infrastructure crack detection
Maintaining the health of infrastructure, such as roads, bridges, sidewalks, and public buildings, is critical for the community's safety, efficiency, and overall well-being.

The models we have in production today would’ve taken us much longer to build on our own and would’ve required more upfront costs,” says Lwowski. “I don’t think there was a faster way to get the data labeled with the quality we needed—and within the time we needed.
Jonathan Lwowski
Lead AI/ML Engineer, Zeitview
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