Energy businesses use AI to forecast generation and demand and to keep distributed assets running. The path starts with the data your sites already produce.
Forecasts that improve scheduling, trading and storage use.
Detecting under-performing panels, turbines and batteries early.
Assembling emissions and performance reports from operating data.
Four stages, each ending with a decision. The first line of every stage is specific to your industry.
Use case scoring
12 assessedOwner: Asset performance lead
Measure: forecast error
Pilot: generation and demand forecasting
Week 4Five sites, 8 weeks
Day-ahead forecast error
Decision: continue
Reviewed with the owner
Connected systems
AI use cases
This quarter55% lower error
Across the portfolio
Solar, storage and efficiency businesses run on equipment spread across many sites. We build the monitoring, analytics and reporting tools that turn device data into uptime, lower cost and numbers you can stand behind.
Tell us about your business and where the time goes. We will come back with the use cases we would assess first and how we would test them.
