JOT VISIONSPOT · POINT CLOUD PROCESSIN
ML-based feature extraction and automatic digitalisation for surveying.
HOW IT WORKS
Point clouds contain an enormous amount of information, but turning that raw data into structured topographic information can require significant manual work.
Instead of relying only on fixed rules, the AI is trained using examples of the features they need to recognize. Through this training process, the system learns the relevant geometric characteristics and parameters and can then apply that knowledge to new point-cloud data.
Whether the job is bulk attribute management, no-code scripting, or turning raw point clouds into GIS-ready features, the plugin suite is the same automation layer behind every project we ship.
01
The model is shown labelled examples of each feature it needs to recognize.
02
Through training, the system learns the relevant geometric characteristics and parameters.
03
That learned knowledge is applied to new point-cloud data as it comes in.
04
Detected features are delivered as structured, ready-to-use topographic data.
THE SUITE
Each plugin targets a different bottleneck — survey automation, no-code scripting, and point cloud object detection.
trainable feature classes, expandable to your own library
Vertical asset
Utility access point
Drainage
Network infrastructure
Vertical asset
Other supported topographic elements
SEE IT RUN
GET STARTED
ML-based feature extraction and automatic digitalisation for surveying — built into your AutoCAD and Civil 3D workflow.
Remote embedded GIS engineering services for global infrastructure operators. Office-based post-processing, deployed in 1–2 weeks.
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