ESG scoring
Structure evidence and automate repeatable scoring workflows.
AI in ESG
Transparent ESG intelligence teams can defend.
AI can automate ESG scoring, monitor sustainability risks and improve benchmarking while preserving the source evidence needed for compliance and accountability.
SECTOR HIGHLIGHT
Scoring
ESG scoring, sustainability-risk monitoring and transparent reporting.
See esg casesThe sector challenge
Production AI in esg 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 esg.
Risk monitoring
Track sustainability signals and emerging risks in near real time.
Greenwashing detection
Compare published claims with external evidence and consistent criteria.
ESG 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 esg? Let's scope it together.
Talk to a solutions architect about the data, validation and delivery path for your use case.
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