The startup develops an energy consumption monitoring system that utilizes machine learning to gather revenue-grade data from electric, gas, and water meters. This technology provides utilities with real-time energy measurements and consumer alerts during peak periods, enabling users to reduce energy costs and consumption.
Funding
$25.6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Utilities often lack real-time visibility into energy consumption patterns at a granular level, hindering their ability to optimize grid management and implement effective demand-response programs. Traditional meter readings provide infrequent data, making it difficult to detect anomalies, predict peak demand, and engage consumers in energy conservation efforts.
Solution
Copper Labs provides a real-time energy monitoring system that leverages machine learning to collect revenue-grade data from electric, gas, and water meters. The system uses non-intrusive sensors to gather high-resolution consumption data, which is then processed using proprietary algorithms to identify usage patterns, detect anomalies, and forecast demand. This technology enables utilities to gain real-time insights into energy consumption, optimize grid operations, and provide consumers with timely alerts and personalized recommendations to reduce energy costs and consumption.
Target Audience
The primary target audience includes utility companies seeking to improve grid management, optimize demand-response programs, and enhance customer engagement.
Features
- Non-intrusive sensors for real-time data collection from electric, gas, and water meters
- Machine learning algorithms for pattern recognition, anomaly detection, and demand forecasting
- Revenue-grade data accuracy for billing and regulatory compliance
- Real-time alerts and personalized recommendations for consumers
- Integration with existing utility infrastructure and data management systems