Data Intelligence for Renewable Energy Operations

Part of Stanford‘s Sustainability Accelerator, Zentus builds the data infrastructure
and AI tools that wind and storage operators need to unify fragmented operational data,
predict asset health, and maximize revenue in evolving energy markets.

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Your Data Has More Value Than You’re Capturing

Growing fleets, fragmented systems, and evolving markets create complexity
that conventional tools weren’t built to handle.

Fragmented Data Platforms

Asset data lives across SCADA systems, drone inspection platforms, repair logs,
and CMS providers—making holistic analysis nearly impossible.

Reactive Maintenance

Without predictive defect models, teams rely on conservative repair schedules
or wait until failures occur—both costly approaches.

Expert Bottlenecks

Blade specialists spend hours manually reviewing inspection images;
valuable technician field insights go uncaptured in databases.

Evolving Market Structures

Ancillary service products, pricing, and eligibility criteria shift faster
than traditional revenue models can adapt.

Warranty Trade-offs

Flexible performance warranties could unlock premium revenue,
but battery degradation impacts remain uncertain.

Forecasting Blind Spots

Missing the extreme price hours that define profitability;
conventional RMSE-based models optimize for the wrong metrics.

What We Build

End-to-end solutions from data pipeline to deployed intelligence

We transform fragmented inspection, SCADA, CMS, and repair data into unified, queryable systems that enable trend analysis and predictive modeling.

Our pipelines handle the messiness of real-world operational data.

Machine learning models trained on historical defect patterns to forecast crack propagation rates, erosion progression, and failure probability distributions

Helping you catch issues before the point of no return.

Scenario-based forecasting tools that model lifetime ancillary service revenue under evolving market conditions.

We quantify degradation trade-offs so you can confidently price flexible warranties and optimize asset specifications.

From LIDAR gust detection to short-term forecasts, we build systems that convert atmospheric measurements into control commands and trading signals.

Helping grid operators and energy traders act on the information that matters.

A Pilot-First Approach to Value Discovery

We don’t sell a black box. We co-develop and validate AI solutions using your real operational data, proving value before you commit to scale.

Reduce asset downtime through predictive maintenance.
Improve revenue capture in volatile markets.
Enable optimal operational and trading decisions.
Unify fragmented data into actionable insights.

Our Collaborative Pilot Process

Define Scope: Identify your specific asset portfolio and operational challenges.
Analyze Historical Data: Conduct comprehensive analysis on your operational and market data.
Co-Develop Prototype: Build and refine a solution adapted to your environment.
Validate and Scale: Test results against real conditions, quantify impact, and scale success.

Proven Track Record

Research Foundations

Experience includes deep collaboration on NREL’s flagship projects, including AWAKEN, OpenFAST, and FLORIS, as well as Stanford, CU Boulder and ForWind.

Industrial Experience

Proven experience through R&D projects with leading wind energy operators in advanced forecasting and operational optimization.

Physics-Informed ML

Models built on domain expertise, optimized for financial and operational outcomes, not just statistical accuracy metrics.

Backed by Deep Domain Expertise

Our team combines decades of experience from NREL, Stanford, and leading R&D projects in wind energy, storage, and machine learning.

Aoife, PhD.

Neural networks & ML
Big data pipelines
Control systems

Juan

Probabilistic forecasting
High-performance computing
Real-time data systems

Ishaan, PhD.

Predictive O&M
SCADA analytics
Field campaign validation

Rafael

Platform architecture
Data engineering
Simulation frameworks

Nicholas, PhD.

Sensing and instrumentation
Reduced order modeling
Data assimilation

Learn More About Our Team

Ready to Turn Your Data into Decisions?

Whether you’re managing blade health across a wind fleet or modeling storage
revenue in evolving markets, we’ll co-develop a solution tailored to your
operational data and business goals.