GridSeer delivers an AI-driven software and analytics platform that improves reliability, reduces risk, and cuts cost in large energy systems.

The key challenge we’re addressing with GridSeer is the difficulty of integrating distributed energy resources for optimized performance. These resources range from wind, solar and batteries in grid applications, to boilers, chillers, steam generators and thermal storage for campus heating and cooling applications and even EV network design for optimized charging and discharging of vehicle batteries. While crucial for a secure energy future, these resources are variable and unpredictable, making it hard for providers and users to optimally balance supply and demand. As energy demand grows, especially as energy assets move more and more to the edge of the grid, the need for smarter energy management tools becomes critical to avoid higher risks, costs, and reduced reliability.

GridSeer uses probabilistic forecasting and risk awareness to go beyond traditional energy system models. Instead of preparing for the “most likely” future scenario, our software evaluates all possibilities, enabling energy providers and users to make smarter, more cost-effective decisions for real-time energy resource deployment.

GridSeer isn’t just a forecasting tool—it’s a decision-making platform. Using machine learning tools, GridSeer analyzes historical and real-time data from energy meters, energy assets and weather patterns. GridSeer predicts load and demand fluctuations and recommends adjustments to optimize the energy system while also reducing reliance on costly backup power.