Powered by Vertical-Specific AI

SEW’s Smart Disaggregation Platform uses AI/ML to provide appliance-level insights, personalized recommendations, and improved customer experiences, while integrating with demand response, EVs, and renewables to optimize load management.
Purpose-built for Utilities using Advanced AI Algorithms
Valuable Insights into Individual Appliance-Level Usage Patterns
Trained on Vast Industry Use Case Coverage
AI-Powered Disaggregation with 87%+ Average Accuracy
AI-Powered Next-Best Action to Optimize Energy Consumption
Data-Driven Personalized Engagement
Integrated with Renewable Energy and Utility Systems
AI/ML-Powered Reports Guided by Behavioral Science
The platform uses AI to deliver Next Best Actions, helping utilities and customers save energy and water.


The platform uses AI and analytics to deliver accurate Next Best Actions, enabling smarter utility decisions and energy and water savings.
Our vertical AI delivers disaggregation insights through dashboards that optimize utility operations and sustainability.


Boost demand response using integrated energy, smart home tech, and digital marketplaces for scalable energy management.

#1 Digital Self-Service Platform
Up To 40% Customer Bill Savings
Best-in-Class In-Built Integrations
Up to 90% Increase in Customer Adoption
Promote Energy Efficiency and Water Conservation
Omnichannel and Personalized Customer Communication
Disaggregation for energy, water, or gas involves extracting consumption data from individual appliances, such as refrigerators, air conditioners, water heaters, and more. The extracted data on appliance usage is then converted into actionable insights for optimizing consumption, detecting anomalies, preventing energy and water losses, and more!
Vertical AI refers to AI specifically trained on certain industry use cases (in this case, the utility industry) to provide highly specialized, context-aware insights and solutions tailored to address industry-specific challenges.
Next Best Action involves providing informed recommendations to customers based on insights derived from their consumption data. This process leverages AI trained on industry-specific use cases to generate and propose the best possible actions for driving energy efficiency and water conservation.

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