This is like giving the electric grid a very smart traffic controller that can predict and reroute power flows in real time so lights stay on and renewable energy is used more efficiently.
Improving power grid flexibility and reliability as more variable renewable energy (like wind and solar) comes online, reducing outages and curtailment while managing demand and supply more intelligently.
Access to real grid operations data, academic–big tech partnership (Texas Tech + Google), and domain-specific models/algorithms for flexibility and demand response that are hard to replicate without similar data and expertise.
Hybrid
Time-Series DB
High (Custom Models/Infra)
Real-time ingestion and processing of high-frequency grid telemetry and market data; ensuring model robustness and safety for grid operations at scale.
Early Majority
Focused on grid flexibility and renewables integration at research scale with direct investment from a hyperscaler (Google), positioning it at the intersection of energy systems engineering and advanced AI/ML rather than being just another generic forecasting tool.