Building & Construction

Building Construction AI. Visibility, Safety, and Efficiency.

Building-Construction

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.

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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.

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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.

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Vladimir Liashenko
Feb 22, 2024
What our Clients are Saying

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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Ready to get started?

In high-stakes environments, AI can’t just be good—it must be right.

Let’s build AI you can trust.