A $33 Million Rehab Program, Built on Data the Utility Could Actually Trust
Before committing to a multi-year rehabilitation program, a large Southwest water utility evaluated five inspection vendors side by side. It chose SewerAI. Across roughly 181,000 linear feet assessed, the data sorted the system into fundable action: about 38% needing CIPP lining, about 2% needing point repairs, and the rest monitored. The result was a $33 million program the utility could defend in front of a board.
When a large water utility in the Southwest set out to plan a multi-year rehabilitation program, the hardest question wasn't how much to spend. It was whether the data underneath the plan was good enough to stake tens of millions of dollars on.
So before committing to anything, the utility did what careful programs do. It evaluated five different inspection vendors and put their data side by side.
It chose SewerAI, and the program that followed shows why the choice mattered.
The data had to survive scrutiny
Across roughly 181,000 linear feet assessed, the inspection data didn't just produce a pile of defects. It sorted the system into clear, fundable action: about 38% of the assessed pipe needed CIPP lining, about 2% needed point repairs, and the rest could be monitored rather than rushed.
Those percentages are the difference between a plan and a guess. A utility that knows exactly which third of its system needs lining can size a program, sequence the work, and defend every dollar of it. A utility working from inconsistent data ends up over-fixing some assets, missing others, and spending the budget meeting explaining numbers it isn't sure of.
A $33 million plan you can stand behind
The result was a $33 million rehabilitation program grounded in data the utility had already pressure-tested against four other options. That's not a small thing to be able to say in front of a board. The confidence to commit at that scale came from knowing the condition picture was verified, consistent, and built to be questioned.
And the contractors who win the lining and repair work run from that same verified data. A program scoped on accurate condition means their crews show up against real, confirmed need, not a stale estimate that sends them to the wrong pipe.
The headline isn't the $33 million. It's that the utility could put that number in front of decision-makers and defend it, because the data it rested on had already earned the trust.
See how the data holds up. Watch the inspection-to-program workflow that lets a utility commit at this scale with confidence.
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