The startup provides big data analytics services that decode real-time electricity consumption at the appliance level by analyzing smart meter data. This enables utilities, appliance manufacturers, and market research companies to gain actionable insights and create data-driven revenue opportunities.
Funding
$330K 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
Many homeowners and businesses lack detailed, real-time insights into their electricity consumption patterns, making it difficult to identify energy waste and optimize usage. Traditional energy audits are infrequent and costly, while basic smart meters provide limited appliance-level data. This lack of granular information hinders effective energy conservation efforts and cost savings.
Solution
Sustlabs offers Ohm Assistant, a smart energy monitoring solution that provides real-time, appliance-level electricity consumption data and actionable insights. The system uses a smart bot installed in the main electrical panel, combined with a mobile app, to track energy usage and identify consumption patterns. Machine learning algorithms analyze the data to provide appliance-specific breakdowns, detect potential electrical hazards, and offer personalized recommendations for energy efficiency. The platform also tracks carbon footprint and provides utility bill predictions, empowering users to make informed decisions and reduce energy costs. For businesses, Sustlabs offers an Energy Management Console (EMC) that aggregates data from multiple areas or equipment, along with continuous power quality analysis.
Target Audience
The primary target audience includes homeowners seeking to reduce energy consumption and lower utility bills, as well as businesses and building managers looking to optimize energy usage and improve operational efficiency.
Features
- Real-time electricity consumption tracking at the appliance level
- Machine learning-based identification of heavy appliances and energy consumption patterns
- Predictive analytics for electrical fire prevention, with alerts sent 15 minutes in advance
- Continuous power quality monitoring and alerts for electrical issues
- Carbon footprint tracking to monitor and reduce emissions
- Utility bill predictions for better energy usage planning
- Mobile app for iOS and Android to monitor energy consumption and receive insights
- Energy Management Console (EMC) for businesses to manage energy consumption across multiple areas
- Historical data access to track daily, weekly, and monthly energy usage