InesPointCloudEngine
Cloud-based point cloud processing engine
Serverless pipelines to process millions of points without building dedicated infrastructure for each project.
Data processing and analysis
A tool designed so that other projects can delegate point cloud processing, usually very costly, without deploying a specific architecture. Tasks are defined as pipelines of generic steps: maximum modularity and work that can be reused across projects.
What it does
01JSON pipelines
Tasks defined with a simple JSON syntax: PDAL steps (fast and proven by a large community) and our own Python functions for calculations PDAL does not cover.
02Multi-project
Modular syntax, parallel processing and scalable architecture: any client tool can use it at the same time.
03Multi-input
It receives jobs via API, Lambda, S3 automations or MQ messages, whichever suits each application best.
04Serverless
All processing runs in the cloud, in a serverless environment: guaranteed availability and easy scaling.
Point clouds
Point clouds digitise reality with very high precision and support inspection, modelling, simulation and terrain analysis. The challenge is processing them: handling millions of points, filtering noise, segmenting structures and extracting information. Processing them in the cloud makes it possible to scale, parallelise and speed things up, and reduces development and maintenance for each new project.
Product screenshots
Where we have applied it
Spain
Railway slope data collection
Integrated data collection system to inspect slopes across the whole railway network.
View project on ines.es
Spain
Innovation in railway bridge inspection
R&D project with ADIF and ERDF funding to find alternatives to traditional bridge inspection.
View project on ines.es
Want to see itin action?
We will show you Ines PointCloudEngine with data and cases similar to yours, and answer your technical questions.