This week we officially released Cognitive Integrity Management™ 3.0, (“CIM 3.0”), which was developed under the product codename Polaris. The product team has been working tirelessly with SME’s from our participating pipeline operators during our private preview to ensure the solution applies horizontally across most operators. Starting at the end of May, each week these SME’s provided us operational data from their existing systems, assisted to validate CIM features, and confirmed the accuracy of the results.
The more time we spend with our clients the more we learn they are reliant on spreadsheets. To this point, we’ve jokingly considered changing our mission from “Predict pipeline failures, save lives and protect the environment… with the assistance of Machine Learning” to “We eliminate legacy Microsoft Excel spreadsheets”. Of course, all joking aside, we want to enable integrity management teams to spend their time doing high-value engineering. The latest Microsoft Excel sheet we have replaced is a customer’s version of a Crack Fatigue Analysis based on the modified Ln-Sec equation for cracks in pressurized pipelines.
During our time in the Microsoft Accelerator, Data Science, and Machine Learning cohort, we interviewed a few folks working in integrity management for pipeline operators to ask them to describe some of their most difficult challenges. We anticipated it would range from dealing with silos of data to spatially integrating risk data. However, we were surprised to learn that they simply wanted a solution that would accurately align features (welds, anomalies, valves, etc.