Zentus provides an end‑to‑end data infrastructure and AI platform that consolidates SCADA, sensor, and market data from wind farms and energy storage assets into a unified repository. Using physics‑informed machine‑learning models, it delivers predictive maintenance alerts, probabilistic forecasts, and real‑time optimization recommendations to reduce downtime and improve revenue capture. The company validates solutions through a pilot‑first process, co‑developing prototypes on the customer’s own data before scaling.
Funding
Funding not disclosed
Founders
Product
Problem
Wind farm and energy storage operators often manage large, fragmented SCADA and market data sets with legacy tools that cannot integrate disparate sources or provide real-time insights, leading to missed maintenance opportunities, suboptimal trading decisions, and reduced revenue.
Solution
Zentus offers an end‑to‑end data infrastructure and AI platform that ingests and unifies operational and market data from wind and storage assets. Using physics‑informed machine‑learning models, the system delivers predictive maintenance alerts, probabilistic forecasts, and optimization recommendations tailored to each asset portfolio. The company follows a pilot‑first methodology, co‑developing and validating prototypes on the customer’s own data to demonstrate measurable value before scaling. Results are delivered through dashboards and APIs that support operational and trading workflows, enabling operators to reduce downtime, capture market opportunities, and make data‑driven decisions.
Target Audience
Primary customers are wind farm operators, energy storage asset managers, and renewable energy trading teams that require integrated analytics to improve asset reliability and market performance.
Features
- Scalable data pipelines that consolidate SCADA, sensor, and market data into a unified repository
- Physics‑informed neural networks for ultra‑short‑term probabilistic wind forecasting and storage revenue modeling
- Predictive maintenance models that identify component degradation and schedule interventions to minimize downtime
- Real‑time optimization tools for wake steering, pitch control, and market trading based on high‑performance computing
- Customizable dashboards and API integrations for operational monitoring and automated decision support
- Collaborative pilot process that defines scope, analyzes historical data, co‑develops prototypes, and validates impact before full deployment