Data Ingestion Pipeline
Verdian Ag operates entirely remotely, relying on multi-spectral and radar satellite networks combined with localized meteorological APIs.
Remote Sensing
We ingest continuous optical and synthetic-aperture radar (SAR) data. This multi-modal approach ensures consistent data collection regardless of cloud cover, allowing for uninterrupted monitoring.
Climatic Inputs
Satellite baselines are enriched with historical rainfall data, 14-day forecasts, and temperature extremes to contextualize the physiological stress observed from space.
Algorithmic Processing
Rather than providing raw vegetation indices, Verdian Ag processes pixel-level data through specialized agronomic models. We model crop stress responses by tracking actual canopy cover growth against idealized logistic S-curves for specific crop types in specific climate zones.
When moisture levels drop below designated threshold parameters, our models apply localized water stress penalty functions to estimate biomass accumulation discrepancies.
Processing Logic Flow
Situational Ground-Truth Integration
Satellite data alone is insufficient for assessing institutional lending risk. A high-yielding crop is a stranded asset if the farmer lacks market access, faces impassable infrastructure, or lacks off-take logistics. Verdian bridges this gap through continuous farmer interaction.
Proximity & Logistics
We algorithmically map the distance from a verified farm polygon to the nearest known processing hubs and markets. However, a map cannot see a washed-out bridge. Through our AI-powered WhatsApp bot, we run conversational loops querying farmers about the actual, on-the-ground conditions of those access routes during harvest season. This grounds abstract spatial data in logistical reality.
Behavioral Verification
The platform verifies crop interventions by cross-referencing farmer-reported actions (e.g., "I applied urea yesterday") via WhatsApp with subsequent NDVI shifts observed from space, establishing a reliable metric of grower honesty and capability.
Structured Data Outputs
Representative Output Schema
The following JSON structure represents the standard data payload generated by the Verdian platform. This is a representative schema intended to illustrate the structure and types of intelligence our models provide to support institutional pre-verification and risk assessment.
{"field_id": "uuid-v4-string","assessment_date": "2026-02-22T00:00:00Z","metrics": {"verdian_score": 82,"confidence_level": 0.88,"vigor_index": {"current_value": 0.65,"7_day_trend": "stable"},"water_stress": {"status": "nominal","estimated_depletion_percent": 35},"compliance_ratio": 0.90},"flags": [{"type": "heat_stress_warning","severity": "medium"}]}