Maintaining water system capacity is crucial and if done wrong, repairs can cost millions of dollars.

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OUR SOLUTIONS

PIPE  AI was developed to enable organisations to move from reactive repairs to predictive asset management and save significant costs by leveraging data and AI. Our end-to-end asset management platform offers peace of mind.

PREDICT FUTURE EVENTS

Pipe failure predictions
PIPE AI analyses current and historical data to make predictions about future pipe failures. 
Your finance and risk teams can leverage the predictions to budget funds for inspection works for the next two years. This allows your company to focus on preventive repairs without disrupting consumers.

Automated asset scoring
Based on age, material and previous work orders, PIPE AI generates a score for each asset and prioritise future inspections. This automated step allows your team to quickly action decisions made.

One-click inspection requests
PIPE AI streamlines your processes. 

With just a click of a button, you can generate inspection requests for assets that require review based on the priority scoring system. 

REVIEW AND DETECT PROBLEMS

ML model training
PIPE AI’s model continuously trains to identify defect classification such as cracks, fine roots, or blockage. Our model can detect over 100 defects across 66 defect families.

Defect detections
By using PIPE AI, the inspection process is automated and works 24/7. Our technology detects up to 15% more defects than a manual review and finds faults that humans missed due to fatigue or subjectivity.

Concise reporting
Access inspection results through a configurable Client Portal. Analytics reports and dashboards present the different types of incidents detected as well as predicted maintenance and repair schedules (repair now, reline in a few years, or leave thanks to good pipe conditions).

KEY BENEFITS

Comply with local standards and codes

Maximise life of infrastructure

Perform complex analytical tasks

Access data in a user friendly platform

Move from reactive to predictive management