Catch the Meters Costing You Revenue
Now Available On-Demand!
Already registered? Click here to log in now.
Would you bet on your meter billing accuracy? Most utility leaders wouldn't, and for good reason. Only one in six trust their numbers. Two-thirds are still replacing meters on age alone, not on evidence. And most have no real read on how much revenue their aging meters are quietly costing them.
That uncertainty carries a price. Under-registering meters bleed billable revenue long before anyone notices, and by the time the meter is replaced, that revenue is already gone.
Join VODA.ai's Cory Sides and Ben Schroeder for a candid conversation on what it actually takes to trust your meter data, and how AI-driven meter accuracy analytics turns that uncertainty into a defensible, revenue-protecting plan you can act on.
Source: VODA.ai polling of utility professionals, Smart Water Summit, September 2026.
Key Takeaways:
- What most utility leaders get wrong about their own meter accuracy.
- Why age-based schedules and random sampling miss the real losses.
- How to translate Volume at Risk into gallons and dollars for confident capital decisions.
- How to catch under-registering meters before the revenue is gone.
- Where to start, using the data you already have.
Speakers
Joe Engram
Director of Sales – Southeast
VODA.ai
Joe Engram has spent nearly 19 years in metering, starting at Itron in 2006. He has held product management, technical support, and sales roles at Red Seal Measurement, Mueller Systems, and Water Works Metrology. Engram has deep expertise in Advanced Metering Infrastructure, machine learning, and system optimization, and helps utilities use their data to make better asset decisions.
Benjamin Schroeder
CTO
VODA.ai
Ben Schroeder is Chief Technology Officer at VODA.ai. With more than 15 years of experience in AI, machine learning, and SaaS product development, he has led teams from early-stage startups to Fortune 500 companies. His work focuses on turning advanced AI research into products that solve real-world infrastructure challenges, helping organizations apply automation, data science, and cost-efficient design to achieve measurable impact.
