Generation forecasting
Forecast variable wind and solar generation with uncertainty.
AI in renewable energy
More reliable renewable generation and smarter grids.
AI applications in renewable energy include predictive maintenance, generation forecasting, energy optimization and smart-grid management.
SECTOR HIGHLIGHT
Maintenance
Predictive maintenance, energy optimization and smart-grid management.
See renewable energy casesThe sector challenge
Production AI in renewable energy has to fit the real operating environment.
Delivery, validation and governance stay explicit from the first data decision through production use.
CHALLENGE
Data reality
Use representative data from the environments where the system will run.
CHALLENGE
Operational fit
Design around the people, tools and constraints already in the workflow.
CHALLENGE
Validation
Agree measurable success criteria and review evidence before deployment.
CHALLENGE
Governance
Keep ownership, limitations and human review points visible.
What we build
AI applications for renewable energy.
Predictive maintenance
Identify equipment risk before it creates costly downtime.
Grid optimization
Balance supply, storage and demand across changing conditions.
Renewable Energy case studies
All
Geospatial AI · MicrogridsIdentifying Optimal Microgrid Sites with AI
Mapping opportunity sites with satellite imagery and machine learning to accelerate rural electrification.
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Energy Forecasting · NorwayPredicting Norway's Electricity Prices with 97% Accuracy
Machine-learning forecasts that support smarter renewable-energy decisions across Norway.
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Solar Adoption · AfricaAccelerating Solar Adoption in Sub-Saharan Africa
AI-powered forecasting for faster solar adoption and improved rural energy access.
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ESG · Greenwashing DetectionDetecting Greenwashing with 85%+ Accuracy
An AI-driven ESG monitoring system that supports sustainable trade and surfaces greenwashing.
Read case studyBuilding AI for renewable energy? Let's scope it together.
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