AI Model Evaluation and Benchmarking
Expert-level environmental science challenge items that stress-test how well LLMs reason about climate, ecology, and forestry.
AI Model Evaluation and Benchmarking
Frontier models sound confident on climate and ecology, then fail on the details that matter — baseline setting, additionality, leakage, the gap between a satellite signal and what is actually on the ground. Generic benchmarks miss this because they are written by generalists. Evaluating environmental reasoning takes someone who has done the fieldwork and the MRV.
The approach
A field-verified method, not a desk exercise.
Deliverables
Benchmark item set
Expert-authored challenge items with rubric-graded reference answers across your target domains.
Capability assessment
A written read on model strengths, failure modes, and the reasoning gaps that carry real-world risk.
Domain breadth
Tropical forestry, REDD+, carbon markets, biodiversity, EUDR/CSRD, remote sensing.
Researcher hand-off
Structured items and notes ready for your AI research or prompt-engineering team.