Automating Point Cloud Classification: How Dielmo 3D Improved Accuracy, Scalability, and Data Quality 
Dielmo 3D delivers topography, digital mapping, and AI-driven data analysis with 20+ years of experience, serving global clients across infrastructure, energy, and agriculture.
Ensuring the model generalizes across diverse environments while maintaining class balance.
Handling sparse data, such as thin structures like wires, without losing accuracy.
Developing a stable and reliable model from scratch for consistent performance.
Dielmo lacked the in-house resources with the required deep learning expertise and faced scalability constraints in developing a robust classification model.
The model demonstrates 84%+ accuracy in classifying diverse environments, ensuring reliable results across various real-world scenarios, with consistent performance even in previously unseen conditions.
The scalable architecture allowed the client to handle larger datasets without the need for significant investment in additional infrastructure, resulting in cost savings of up to 50% in hardware and IT resources as the business grows.
