RailLinks Predict facilitates the creation and execution of individual analytical plugins. These plugins are able to request data, perform a process, and store results either for consumption or further processing. A series of plugins can be sequenced together to perform a workflow, enabling users to create variations on processes according to specific business requirements. Workflows can be scheduled or triggered on certain events, such as receipt of new data or completion of a scheduled job. Using our state-of-the-art architecture, you can run hundreds of jobs in parallel to complete weeks of processing in a few minutes.
Cloud Workflows also integrates seamlessly with RailLinks® AI, a dedicated engine that uses artificial intelligence to solve unique railway inventory (in-service) and condition problems. Complementing scientific tools that are working together to provide solutions.
Flexibility is a valued attribute. Our plugin framework empowers engineering teams to scale computing power and storage resources to the requirements of the analytical job being performed. Our on-demand architecture ensures those resources are only in use for the time required to execute the intended analysis. RailLinks Predict can run operations in a variety of scientific frameworks, whether COTS (commercial off-the-shelf) or open source, and in a variety of operating systems. Our plugin creation interface facilitates the creation, parameter setup, and routing of the plugin. And because flexibility is at our core, organizations can schedule jobs to their own computing resources, taking full ownership over proprietary code.
Plugin execution is also flexible and can be run on-demand, on a schedule, or triggered on a data ingestion event. Did we mention flexibility? Data transmission can be performed Cloud to Cloud, On Site to Cloud, or Edge to Cloud.
Our architecture offers a repository of any data type, including imagery, linear sampled measurements, point clouds, and textual events. With this foundation, RailLinks Predict allows data scientists to look at the parts in a holistic approach to find root cause. This requires precisely organized, multidimensional data sets, which can be called upon through a safe access API. As RailLinks Predict works on condition event data, it can further organize the Lake, by tagging specific data sets with custom attributes.
Our stunning interactive reports let you jump right to the interesting spots in your network, compare the analysis with actual condition data, and generate forward-looking action plans with estimated costs.
Create beautiful dashboards to track key KPIs. Data sources integrate directly into our platform and cloud workflows. Contact us directly for more information on our current library of plugins and interactive reports.