Cognitive Integrity Management
- Ingest all pipeline inline inspection data fast. Disruptively fast.
- Library of proprietary Machine Learning algorithms revolutionizes the modeling of corrosion growth.
- Automatic dynamic 3-D pipe visualizations thematically illustrate corrosion growth.
- Augmented reality using HoloLens.
Our cloud-based Machine learning algorithms provide supercomputer performance to automatically align pipeline features across your enterprise. Fast. Insanely fast.
Provides business intelligence on a real-time basis, including visibility into pipeline segments and pipe joints with the most critical areas of corrosion. Drill down to study specific anomalies aligned in multiple ILI datasets, to view their patterns in 3-D mode or to correlate their physical location in the real world using Google maps and Street View. This all contributes to better business decisions.
- Machine Learning algorithms learn and become more intelligent as they process more data. No manual coding or other software required.
- Our multiple algorithms increase the predictive capabilities by including additional data sets such as soil type, land use, annual rainfall, CP data, pipe coating type and other off-pipe data.
Addressing key elements of RP1163 for the industry
- Instant validation of inline inspection performance in accordance with RP1163.
- Inline inspection performance specifications are validated and modeled using Machine Learning.
A new experience
- Our new spatial engineering environment blends geospatial and traditional inline inspection data capabilities within a single, all-inclusive product.
- Master all data in tables, vector geometry, 3-D on pipe imagery, and maps.
- Command multiple sources at once to blend, prepare, extract, transform, load, analyze, validate, visualize and explore data.
- Transform data using the awesome power of the Microsoft Azure cloud.
Request a live, one-on-one demonstration today!
Coming in the near future: Public Awareness and Emergency Response Management. These products will be available for demonstration in November or December 2017. Please continue to check back here for news on these products which will be released from time to time.