Accuracy and evaluation
How GeoPard measures AI Assistant accuracy and validates generated plans.
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How GeoPard measures AI Assistant accuracy and validates generated plans.
We measure the assistant's agronomic accuracy on a versioned benchmark. We publish every category score, including areas still improving.
503 expert-level agronomy questions, CCA-style.
Five categories: soil and water, crop management, nutrient management, pest management and IPM, precision ag specialty.
Versioned and re-run on releases. Current version: v2, July 2026.
Precision ag specialty
100%
Soil and water
95.8%
Crop management
93.8%
Nutrient management
92.9%
Pest management and IPM
77.5%
Public benchmark questions leak into AI training data. Once that happens, scores stop measuring capability. The question set stays private so future scores remain meaningful. We publish the methodology, all category scores, and sample questions on request.
Benchmark scores measure knowledge. Every generated plan is dry-run validated before creation. Checks cover nutrient balance and removal coefficients against extension recommendations. They cover soil-test critical levels and build-up conventions from your lab. They also cover application rate limits, setback distances, and knowledge base rules. If a check fails, no map is generated.
The assistant supports professional judgment. It does not replace a certified local agronomist. You review and approve every prescription. Validate recommendations against your crop plan, soil tests, product labels, and local regulations.
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