by combining machine learning algorithms and remote inspection, we scan through terabytes of data to make sure that you have complete control over the health of your physical assets.
We use unsupervised, supervised, and generative algorithms to automatically scan through billions of images.
Our digital inspectors manually remove false positives so that you can focus on the actual damages.
By continuously annotating images and retraining the algorithms, the solution becomes almost automatic with only a tiny amount of expert supervision.
We integrate our software into your systems to run algorithms in real–time and report damages directly to your asset management system.
We're analyzing billions of images and have found hundreds of damages.
A broken catenary wire can stop the train traffic for hours and cost millions. With Infranord and their measurement train, we use DeepInspection to scan 20 000 km of railway in Sweden. In 2021, we analyzed over 500 M images and found more than 150 damages.
Small cracks in concrete sleepers can soon evolve and cause dislocation of sleepers and the rail. In extreme cases, it can lead to derailments. To avoid this outcome, we use DeepInspection to detect and classify cracks early in their development to make sure cracked sleepers are changed.