The silent, decentralized revolution of home energy—driven by mass adoption of rooftop solar and high-load Electric Vehicles (EVs)—has inadvertently created a crisis of confidence for utilities. The distribution grid is now operating with critical “blind spots,” where engineers cannot see the rapid, volatile energy flows that cause voltage instability and threaten system reliability.
Sense, a leading force in grid edge intelligence, has announced a foundational change to how this visibility is achieved. Their new Load Visibility Solution, leveraging proprietary WaveformAI embedded in next-generation AMI 2.0 smart meters, moves beyond simple consumption tracking. It delivers granular, real-time insights that can detect, classify, and precisely map every significant appliance and Distributed Energy Resource (DER) operating behind the meter.
This technological pivot allows utilities to switch from generalized, costly infrastructure upgrades to surgical, proactive management.
“With real visibility into what’s happening at the intersection of the grid and the home, utilities can take control of the most unpredictable part of distribution,” said Sense CEO Mike Phillips. “They can target investments where the grid is most vulnerable, respond faster to emerging issues, and design smarter programs that actually reflect how homes are using and generating energy.“
To understand the core mechanics and future implications of this system—particularly for managing massive EV and solar integration—we sat down with Nancy Riley, SVP of Product at Sense, for a deep technical dive.
Q&A: Sense SVP of Product Nancy Riley on WaveformAI and the Future of Grid Intelligence
Section 1: The Core Technology and Immediate Value
Q1: Defining AMI 2.0 The introduction of Waveform AI signals a clear step beyond traditional Advanced Metering Infrastructure (AMI). Can you describe the primary difference between the standard data retrieved from AMI 1.0 systems and the high-fidelity, actionable intelligence that Sense’s Waveform AI provides to utilities?
With AMI 1.0 systems utilities get interval data—15‑minute, 30‑minute or perhaps even one‑minute snapshots of consumption. You see “how much,” but you don’t see the nuance of how the energy flows, what types of loads are in operation, or the second-by-second dynamics behind the meter. By contrast, Sense’s Waveform AI is embedded in enabled AMI 2.0 meters and captures high‑resolution waveform data (up to 1 MHz of sampling) for much richer information. Because the AI runs directly on meters at the grid edge, we don’t wait for data to travel to the cloud for processing and delivery. Instead we generate real‑time, granular insights like which appliance turned on, when, how much energy it’s drawing, and in some cases even fault or anomaly detection.
In short: AMI 1.0 = “how much was used every interval.” Waveform AI = “what was used, when, how, and why—with precision and immediacy.” This difference matters because it shifts from retrospective billing or simple usage dashboards to actionable visibility at the grid‑edge and in the home.
Q2: Operational Impact Grid visibility is a major theme of this innovation. What is the single most critical new operational insight that utilities gain from this enhanced visibility, and how does it translate directly into cost savings or improved reliability for a typical utility operator?
The most critical new insight that Waveform AI provides is detailed, granular load visibility at scale across the meter population. This allows utilities to identify demand growth and patterns of usage that were previously invisible. For example, a utility can now identify EVs and heat pumps, measure when and where they drive high usage, and pinpoint where these new load patterns are stressing the capacity of transformers and other grid assets. This translates into direct operational benefits: outages can be prevented before they happen, capital investments in infrastructure can be deferred or optimized based on more accurate forecasts, and electrification and demand flexibility efforts can be far more targeted and effective. Ultimately, it’s about moving from reactive to proactive grid operations, which both reduces costs and improves service reliability.
Q3: Solving the Blind Spots Before this level of AI-driven analysis, where were the biggest “blind spots” in the distribution grid? What challenges were utilities simply unable to address with older data streams that they can now tackle with Waveform AI?
One of the biggest blind spots in the distribution grid has been the lack of detailed visibility behind the meter. Traditional systems couldn’t detect which devices were in use, which made it difficult to distinguish between load types or identify when distributed energy resources like EVs or rooftop solar were active. This limits a utility’s ability to accurately track load growth and its impact on assets, target their programs, and use real data to drive detailed forecasting for maintenance and investment planning.
This blind spot also prevented utilities from deeply engaging their customers in electrification, energy efficiency, and load management efforts. With detailed visibility, utilities and consumers can work together to strengthen grid reliability and sustainability.
Section 2: Market Drivers and Sustainability
Q4: The Urgency of Change Why is this enhanced level of grid intelligence suddenly necessary now? Is the rapid adoption of Distributed Energy Resources (DERs) like solar, or the rise of Electric Vehicle (EV) charging, the primary driver for this technological shift?
The need for grid intelligence has become urgent because the energy landscape is shifting faster than utilities can adapt using traditional tools. The rapid rise in EV adoption introduces large, unpredictable loads that can vary widely between neighborhoods, homes, and even hours of the day. Similarly, the growth of distributed solar and other DERs means that energy is now flowing in two directions on the grid, often with little visibility or control from the utility side. These dynamics are not just adding complexity, they’re creating real operational risks if not managed properly. Legacy systems lack the speed and resolution to analyze and manage these challenges. Waveform AI addresses this by giving utilities the granular and timely insights needed to manage new types of load, integrate clean energy, and operate the grid with greater agility. The timing is critical—these challenges are no longer hypothetical. They’re here now.
Q5: Enabling Sustainability The shift to a cleaner grid is a core sustainability goal. How specifically does Waveform AI help utilities integrate a higher volume of clean energy sources (like solar and wind) and manage the increasing strain of localized EV charging without causing system instability?
Waveform AI plays a foundational role in enabling a cleaner, more distributed energy system by providing the precision and immediacy needed to keep the grid balanced. By analyzing waveform data in real time, utilities can detect when DERs like rooftop solar are exporting energy, how much they’re contributing to local loads, and how that affects voltage and power quality on the grid. This helps utilities proactively address issues like equipment stress.
Going deeper on the EV example, Waveform AI identifies when and where EV charging occurs regardless of charger type (Level 1 and Level 2 chargers, any brand). This allows utilities to understand cumulative demand patterns and implement flexible programs like off-peak charging incentives. With this level of insight, grid operators can shape load in a way that aligns with renewable generation peaks, reduces strain on infrastructure, and avoids costly upgrades. In short, it enables a smarter, more sustainable grid by turning uncertainty into actionable intelligence.
Q6: Customer-Centric Benefits Beyond utility operations, how does this technology impact the end consumer? Does the data derived from the meter ultimately lead to new programs, better rate structures, or a more reliable experience for homeowners and businesses?
Yes, the benefits of Waveform AI extend directly to consumers. Because the technology identifies individual devices and usage patterns, utilities can offer more personalized and relevant programs such as EV-specific rates, home energy insights, or incentives for shifting usage to off-peak hours. Consumers gain visibility into their own energy behavior through platforms like the Sense Home app, which helps them make smarter choices and reduce waste without sacrificing reliability or control.
Pushing the depth of intelligence in Waveform AI to the grid edge creates a whole new kind of synergy for residential customers and utilities. End consumers are individually empowered to make informed choices to save energy and reduce costs. When aggregated across homes, that detailed data allows their utility to improve grid reliability, plan accurately to keep pace with load growth, and reduce operating costs – all of which clearly benefit consumers.
Section 3: Product Strategy and the Future
Q7: Product Roadmap As the SVP of Product, how do you see the enhanced data intelligence from AMI 2.0 changing Sense’s long-term product roadmap over the next three to five years? Where is the ‘next frontier’ for utility data intelligence after full adoption of Waveform AI?
Sense’s current solutions for utilities focus on grid visibility. The logical next step is to drive deeper into grid management. The insights unlocked by Waveform AI can enable real-time detection of faults, early warnings of potential outages, and smarter demand-side coordination.
Detecting potential and actual faults on the distribution grid is a major driver of utility operating cost and risk. This encompasses targeted efforts like vegetation management and wildfire risk mitigation as well as overall outage management and detection of more subtle issues like floating neutrals, arc faults, or inverter instabilities before they cause equipment failure. The grid edge intelligence of Waveform AI isn’t limited to load disaggregation – it can analyze the high resolution signals from multiple meters to detect, locate, and classify anomalies on the grid. This kind of situational awareness simply wasn’t achievable with older, lower-resolution AMI data.
Q8: Advice for Executives For utility executives who are still relying on traditional AMI systems but recognize the need to prepare for the energy transition, what is the most important piece of advice you would offer them regarding their data and grid modernization strategy?
Taking the 10,000 foot view, the detailed analysis and advice published by EY earlier this year really resonated for me. They highlighted the need to invest in foundational IT infrastructure to fully realize the benefits of AMI 2.0. A holistic strategy must address building enough capacity to collect, transmit, process, and distribute the quantity and granularity of data that AMI 2.0 can provide, and it must prioritize seamless integration of this data into other grid technologies like the advanced distribution management system (ADMS), DERMS, and outage management system (OMS).
From a more Sense-specific perspective, I would encourage executives to lean into the power of partnering with their residential customers to drive decarbonization and to ensure reliable distribution in a world of unprecedented load growth. With aligned incentives to reduce and/or shift demand to support grid reliability and to lower generation-driven emissions, the relationship between people, homes, and the grid can be transformed for a better future.
Q9: The Sense Difference What is one final message you want utility professionals to understand about how Sense is uniquely positioned to help them transition their grid to handle the complexities of the modern energy landscape?
Utilities have historically viewed each side of the meter as clearly defined and separate features of the energy system. The grid side, or “front of the meter”, covers everything from the cables in the ground to the lines overhead. The consumer side, or “behind the meter”, has sat firmly apart from the grid. AMI 2.0 allows smart meters to live up to the potential of their position at the intersection between grid and consumers. Suddenly thousands of smart meters can form distributed sensing, compute, and control platforms fit for the modern grid.
Sense sits directly at that intersection – we embed high-resolution sensing and edge computing into the meter to analyze the data in an instant. Our ability to connect to WiFi and/or cellular networks adds real-time networking, enabling us to deliver timely, actionable insights to both the utility and to consumers. The long-term and unparalleled grid visibility offered by AMI 2.0 with embedded intelligence breaks down the barrier between grid operations and consumer energy use, creating a unified, responsive energy ecosystem.
The Final Word: Transforming Data into a Decarbonization Roadmap
The core promise of Sense’s Waveform AI is not just better data—it’s the transformation of raw information into a clear roadmap for the future. As utilities navigate the mandatory demands of electrification, precise visibility into where and when load is peaking is the only way to surgically allocate capital, defer unnecessary upgrades, and maintain system health. By empowering the smart meter to act as an intelligent, high-resolution sensor, Sense is providing the essential foundation required to transition the world’s grids into a truly smart, responsive, and sustainable energy network.
