Inframark’s Waterminds 360
Inframark delivers clean, reliable water to communities by equipping public utilities with the tools to collect, treat, and distribute water efficiently to households across America.
Now, they are advancing water utility software into the future with "Edge" onsite devices that leverage machine learning to predict issues—such as broken pipes, chemical imbalances, or water flow disruptions—before they even occur. We call this ML predictive learning, and it is the future of Utilities. Now, unforeseen catastrophes can be seen, and fixed, with a great savings in both cost and damage control.
Roles:
Product Design
Team Lead
Engineering Front End Oversight
The Challenge:
As a trusted leader in the utilities industry, Inframark is well-positioned to lead the next generation of water utility software. However, the challenge lies in developing a platform that leverages advanced technologies like data analytics and machine learning—while remaining intuitive, cost-effective, and familiar enough to convert users accustomed to traditional, lower-tech solutions.
The Solution:
Design a modular water utility platform that combines advanced data analytics and machine learning with the trusted familiarity of traditional systems. The UX bridges innovation and convention—introducing powerful new features while upholding industry standards users rely on.
Unique utilities demand versatile solutions.
Real Time Data Widgets and Custom Dashboards
After establishing a baseline style guide and component library, the UX team focused on transforming raw Edge data into actionable software experiences—centered around alerts, performance insights, and predictive analytics.
Configurable, versatile widgets became the core UI pattern, supported by clear user cues that draw attention to critical issues in real time.
With clear, customizable widgets and dynamic dashboards, each utility gets a tailored experience—meeting unique needs with precision and ease.
Predictive Machine learning
With a standard set of widgets and patterns in place, we faced a critical next step:
How do we introduce machine learning in a way that feels intuitive, useful, and trustworthy—without overwhelming users?
The product was evolving beyond data display into prediction and automation. But for many users, this shift could feel abstract or even intrusive. We needed a way to surface machine learning insights that enhanced the existing workflow, not disrupted it.
Following our Widget Dashboard pattern, we designed a dedicated widget experience for predictions—one that adapts fluidly to the prediction window and entices users who haven’t yet explored this new feature.
The user journey begins on the dashboard, where a teaser for the predictive widget is always visible—even for those not yet enrolled. This subtle yet strategic placement raises awareness, sparks curiosity, and encourages users to explore the benefits of upgrading. By integrating the teaser into their daily workflow, we create a seamless entry point that promotes adoption without disrupting existing routines.
The linked chemical page then offers deeper information and operational insights.
The Custom Dashboard acts as a gateway to the machine learning feature
The Machine Learning Widget offers a forecast for upcoming trends
This drill down widget offers deeper data and longer trends.
Unexpected Challenge: How can we confirm that technicians acted on our prediction and applied the chemical dose on-site?
Through this widget, operators know levels should soon adjust
Since sensors can’t detect chemical level shifts instantly, how can we effectively bridge old and new paradigms to maximize user impact?
By exploring other detection models, I found that pumps running at higher speeds often signal the introduction of a new chemical batch. Pairing this insight with our prediction model via an added widget indicates that adjustments are underway—and that predictive levels will soon reflect the change.
Bringing it all together.
Through this widget, operators know levels should soon come down in the negative trend.
Inframark’s WaterMinds bridges legacy systems with modern design, giving utilities a flexible new tool to reduce costs while ensuring reliable, consistent service for water consumers.
All the essential needs of traditional SCADA systems are met—without the clutter—delivered through modern usability and seamlessly integrated with the intelligence of tomorrow: AI.
Testimonials
“I had the great good fortune to work with Dawn when she joined our team to assist with a UI/UX design project that was struggling in terms of clarity, vision, and deliverables. She was the primary driver to resolve all three issues, completely reworking the UI, building out innumerable mockups and prototype designs, and providing constant feedback and oversight to the dev team to build what she was creating.
Throughout the process she was a delight to work with. She had all sorts of great suggestions, gave great and thoughtful feedback, and has an focus on detail that makes all the difference in great UIs. I’m really glad she was part of our team and our product reflects so much of her hard work and talents.”
“I had the pleasure of working with Dawn at Inframark: Her impact on our SaaS project helped us dramatically accelerate deployment. She quickly got to work, recognizing the strong elements of the existing design while thoughtfully reworking areas that needed improvement. Her ability to balance aesthetics with functionality ensured that the final product was both visually appealing and highly effective. Beyond design, they played a crucial role in development, seamlessly collaborating with business leaders, offshore developers, and ML teams to bring the vision to life. Their dedication, adaptability, and problem-solving mindset made a real difference, and I’d absolutely recommend them for any design-driven role.”