WEBINAR

Renewing the Northeast’s High-Risk Water Infrastructure Under Uncertainty

Many utilities still rely on pipe age or past break history to guide infrastructure renewal—but those methods often miss the pipes most likely to fail next. In this webinar, experts from VODA.ai and Arlington Heights share how AI-driven risk prediction helps utilities identify hidden leaks, failing pipes, and underperforming meters to make smarter, data-driven investment decisions.
April 23, 2026
6:00 PM UTC
1 hour

April 23rd, 2026
Time: 2:00 PM ET | 1:00 PM CT | 11:00 AM PT
Duration: 60 minutes
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Summary

Utilities across the Northeast operate some of the oldest and most complex water systems in the country. Pipes installed 70-100, even 120, years ago still serve dense cities where every main break disrupts traffic, businesses, and critical services. At the same time, utility leaders must plan renewal programs with limited budgets, incomplete asset data, and growing regulatory pressure.

Many systems still rely on pipe age or past break history to guide renewal decisions. But those methods often miss the pipes most likely to fail next.

In this webinar, VODA.ai’s Northeast water expert Chuck Krohg, AI expert CTO Ben Schroeder and guest speaker Scott Schweda, Superintendent of Utilities at Arlington Heights, will show how utilities are using AI-driven risk prediction to make smarter infrastructure decisions. Using real examples from the field, they will explain how data can identify which pipes are most likely to fail, where hidden leaks may be occurring, and which water meters may be under-registering and contributing to apparent losses.

The session will show how utilities can move from reactive repairs and age-based replacement to a more defensible, data-driven approach to renewal planning.

Key Takeaways:

  • How AI models work to predict failures.
  • Why pipe age or break history are poor predictor of future failures.
  • How predictive analytics can help utilities prioritize renewal investments.
  • How utilities can identify hidden water loss and underperforming meters.
  • Practical steps for getting started with predictive analytics using existing utility data.

Speakers

Benjamin Schroeder

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.

Chuck Krohg

Chuck Krohg

Director of Sales Northeast

VODA.ai

Chuck Krohg is an engineer specializing in smart water technologies and data-driven decision-making. He works with utilities to improve system planning, reduce failures, and extend asset life through AI-powered risk modeling and asset management. At VODA.ai, Chuck helps connect advanced analytics with practical infrastructure strategies, bringing innovative tools into real-world utility operations.

Scott Schweda

Scott Schweda

Superintendent of Utilities

Village of Arlington Heights

Scott Schweda is Superintendent of Utilities for the Village of Arlington Heights and a seasoned water utility leader with more than 20 years of experience in utility operations and infrastructure management. Before joining Arlington Heights, he held multiple leadership positions throughout water systems in the Chicago Area. Scott brings a practical, field-informed perspective on how utilities can use AI to support better infrastructure planning and decision-making.

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