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Unbiasing your Service Line Material Prediction Model
It is essential for water systems to construct predictive models using unbiased representative data to harness the potential of predictive modeling as a potent tool.
The 10 Principles of Responsible AI for Water Utilities
Responsible AI ensures water utility AI systems are designed, developed, and deployed with ethical considerations, transparency, fairness, and accountability.
Cybersecurity Implications for Managing Lead Service Line Inventory Data
Water utilities must balance the cybersecurity implications with managing lead service line inventory data, whether you decide to build your own system or buy one.
Check out this Q&A on utility communications featuring two of the water industry's leading marketing and communications professionals, Andrea Hay and Kelley Dearing Smith.
Build or Buy? Service Line Inventory Options to Consider
Is it better to build your own or buy a service line inventory system? We explore what needs to be included to comply with EPA lead and copper rule revisions regulations.
Celebrating our First Year, Inviting all to Climb Towards Digital-first Resiliency
Trinnex officially marks one year of working towards solving the most challenging water problems with digital solutions and digital-first resiliency strategies.
Can You Use Machine Learning Reliably to Develop LCRR Inventory?
Machine learning has received mixed reactions from the water community. However, it does show promise in helping with predicting lead pipes to help prioritize verifications.
Webinar Recap: leadCAST for Lead Service Inventories and Mapping
The Association of State Drinking Water Administrators (ASDWA) conducted a webinar about technologies, like leadCAST, for lead service inventories and mapping.
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