Improved decision-making and optimized resource allocation up to 30%
postprocessing work automation helps to better decide when and where to allocate resources for railway infrastructure maintenance as well as save up to 30% of admin and salary costs by decreasing human work involvement
Improved Rail Operational Efficiency through Machine Learning Solutions
Combining deep data science expertise and innovative development techniques, Intetics delivers ML-powered solutions for revolutionizing the way railway companies approach feature extraction and further change analysis.

Challenges We Solve
Long and expensive manual processing of inspection results prevents detecting and addressing railway infrastructure issues on time
High costs and efforts on creating and maintaining in-house ML expertise to develop solutions for inspection data processing automation
The involvement of manual labor increases the risks of human-related errors during the inspection process
The limitations of data types used in existing data automation tools
Cooperation Workflow
Based on the available equipment as well as the requirements for inspection results, Intetics develops ML-based solutions for automated feature extraction and further change detection analysis by measuring tolerances and identifying critical changes within each railway asset.
Data Analysis
Data Cleaning and Preprocessing
Feature Assessment
Model Training & Evaluation
Post-processing work
Benefits and Results
Increased accuracy level
the possibility to train algorithms using several data sources provides higher quality and more regularity in the analysis of rail assets statePredictive maintenance capabilities
the ability to automatically analyze and predict when maintenance is needed reduces the need for manual inspections and increases the efficiency of maintenance operationsFlexible development approach
algorithms development with Intetics remote in-sourcing team is 30% cost-effective in comparison with building relevant in-house expertise
Featured Case Studies
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