Innowatts provides an AI‑enabled SaaS platform that ingests smart‑meter and AMI data to deliver real‑time, high‑resolution load forecasts, demand‑response insights, and customer‑level analytics for electric utilities and energy retailers. By applying machine‑learning models and scenario simulations, the platform helps operators anticipate demand fluctuations, mitigate extreme‑weather risks, and support net‑zero planning through interactive dashboards and API integration.
Funding
$50K 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.
UDFounders
Product
Problem
Utilities and energy retailers often lack real-time, high‑resolution data and predictive analytics needed to anticipate demand fluctuations, integrate distributed resources, and respond to extreme weather events, leading to inefficiencies, reliability risks, and missed sustainability targets.
Solution
Innowatts offers an AI‑enabled SaaS platform that ingests grid‑edge data such as smart‑meter and AMI readings to generate real‑time load forecasts, demand‑response insights, and customer‑level analytics. The platform applies machine‑learning models to predict consumption patterns, identify peak‑load risks, and simulate the impact of distributed energy resources. Results are delivered through interactive dashboards and APIs, enabling utilities to make proactive operational decisions, improve grid reliability, and support net‑zero initiatives. By providing granular, actionable intelligence, Innowatts helps energy providers transition from reactive to predictive management of their networks.
Target Audience
Primary customers are electric utilities, energy retailers, and grid operators seeking advanced analytics to improve demand forecasting, reliability, and sustainability outcomes.
Features
- Real‑time ingestion and normalization of smart‑meter and AMI data at the customer level
- Machine‑learning based short‑term and long‑term load forecasting with weather and event adjustments
- Scenario modeling for distributed energy resources, demand‑response programs, and net‑zero planning
- Interactive web dashboards and API access for integration with existing utility systems
- Automated alerts for extreme weather impacts and grid stress conditions
- Cloud‑native architecture ensuring scalability and data security