transit space monitoring and planning

Tie and Track Inspections

Cordel offers a flexible and powerful architecture to assist networks in capturing and processing track-based imagery data with positioning data, using powerful Machine Learning models to improve the accuracy, reliability and usability of track & tie visual condition reporting. Measuring skew and tie spacing allows the system to report on exception of potential defects quickly and affordably.

Rail, Turnouts & Switch Inspections

The ability to carry out regular track-level inspections with minimal impact on track velocity is imperative to a safe and efficiently operating railroad network. Our platform enables routine inspection of track and ties (sleepers) using our Machine Learning-powered visual inspection systems. We tightly integrate our platform with our customers’ location referencing systems.

We leverage both GPS and Linear Referencing Systems so that every defect is assigned a unique location on the ground that can be easily referenced by customers using their native systems and languages. Our process is cost-effective, repeatable, and easy to validate, and significantly reduces the amount of track walking required for track assessments and inspections.

How Automated Inspections Work

1. Capture or Supply Imagery

Collected using Cordel sensors or uploaded by the customer.

2. Machine Learning

Analyse data using the Cordel Pixel Classifying ML Engine.

3. Human-in-the-loop

Triage inspection results for desktop review by a trained operator.

4. Produce Reports

Export inspection results into Enterprise Asset Management system.


rusted railway tracks

Imaging System-Agnostic Data Processing

The Cordel platform can ingest all forms of imagery and positioning data, including data from commonly available track imaging systems from well-known providers.

track and tie inspection results

Rail-Native Machine Learning

Our machine learning pixel classifying technology was built entirely in-house alongside railroad engineers. We build and train remarkably powerful rail-specific ML models that improve over time and can be easily modified based on regional and customer specifications.

track and tie inspection from aerial view

Powerful and Intuitive Inspection Review

The pixel classifier detects exceptions and queues them for review in our user-friendly and intuitive cloud-based inspection software.

tie inpection

Comprehensive Reporting Based on Engineering Standards

We appreciate that each network has unique engineering standards. So we developed a bespoke process that matches and aligns data outputs from our system to fit each customer's engineering standards.

track and tie inspection map

API Integration with GIS and EAM Software

Once inspections are complete and the human-in-the-loop inspection verification process is completed, the resulting data can then be exported via API, JSON or CSV to our software partners.

Improved Inspection results

A thorough inspection requires the collection, processing, and review of enormous amounts of raw data. By automating the first two steps and using ML to potential flag anomalies, we enable your professionals to spend their time where they're most valuable: making decisions and taking action.

Improved defect ratings

In addition to detecting defects, our machine learning technology can apply estimated condition and severity ratings, enabling us to rank defects by priority when delivering to your technician.

Integrated data outputs and reporting

Data outputs and reports are created automatically delivery engineering-grade reports and alerts via an exception to the relevant operators. Each data layer can be customised to specified engineering standards and requirements

Transform your infrastructure inspections

Visit our contact page to get started today or book a demo to give us the opportunity to show you first hand how we enable deeper insights into critical infrastructure.