Sensing, AI, and engineering — working as one system.
AllAiz is not an AI product with an engineering wrapper. It is an engineering system that uses AI where AI is the right tool — and engineering judgment everywhere else.
How we think about the technology.
AI accelerates analysis — it does not replace engineering judgment. A human engineer is responsible for every recommendation.
The sensing approach is matched to the decision being made — not to what is easiest to collect.
Models trained on infrastructure-specific datasets. They understand what they are looking at.
We deliver condition indices, priority rankings, and schedules — not data files that require another team to interpret.
Data becomes intelligence through engineering.
Mobile LiDAR and imaging capture infrastructure conditions at engineering resolution. Sensor selection matched to the specific assessment type.
Point clouds are registered and cleaned. Images processed through distress detection models. All outputs validated before leaving the pipeline.
Condition reports, priority maps, and digital documentation delivered in formats engineers can act on — not data exports requiring further analysis.
The tools. And why we chose them.
CHCNAV survey-grade mobile LiDAR. Produces engineering-grade spatial data at 21.7× the point density of conventional survey methods.
Large vision-language models for infrastructure distress detection. Classifies crack types, measures severity, maps defect location.
Structured 3D documentation of infrastructure assets. Built for remote navigation, stakeholder briefing, and condition handover.
Proprietary processing pipeline converting raw sensor data into condition indices, defect classification, and maintenance priority outputs.
Want to understand the technical approach in detail?
We are happy to walk through the method, the validation data, and how it applies to your infrastructure.
Request a Technical Discussion