Quantiscan: A Local-First Solution for Point Cloud Processing

Greetings, everyone! Following our initial announcement video, we’ve created a comprehensive overview of Quantiscan’s architecture to address some of the questions we’ve received. It has been great to see the community’s interest in our project and hopefully this video will help clear up any questions you may have.

Watch the Full Presentation

In this video, we explain:

  • What makes Quantiscan different from cloud-first alternatives (QS does still support cloud resources, however)
  • The benefits of our local-first processing approach
  • How Quantiscan handles large datasets efficiently
  • A demonstration of building a digital grid with our tools
  • The future roadmap for Quantiscan features

Key Takeaways

If you’re short on time, here are the main points:

  1. Local-First Processing: Quantiscan runs on your desktop, keeping your data on your machine for better security, privacy, and performance.

  2. Speed & Efficiency: Our application can handle files of nearly any size, from small MB LAZ files to massive multi-billion+ point datasets.

  3. Practical Solution: Designed to work on everyday devices without requiring specialized hardware or complex licensing.

  4. Powerful Features: Beyond just viewing point clouds, Quantiscan offers tools for creating digital twins, classifying data, and integrating with other systems.

We’re excited about Quantiscan’s potential and committed to keeping you updated with regular content. If you work with point clouds, digital twins, or spatial data, we invite you to try Quantiscan.

Have questions after watching the video? Feel free to reach out to us directly.

This video presentation provides a comprehensive overview of Quantiscan’s architecture and capabilities. For the most detailed understanding of our technology, we recommend watching the full video.