TerraVision Analytics fuses satellite imagery, drone telemetry, IoT sensors, and AI into a single edge-native platform — delivering real-time geospatial intelligence across millions of agricultural acres for USDA, agribusinesses, and food-security agencies.
Trusted by leading agricultural & federal institutions
Six integrated capability pillars power the TerraVision Analytics platform — from raw sensor data to decision-ready intelligence products.
Fuse Sentinel-2, Landsat-9, PlanetScope, and private SAR archives into time-series composites. Near-daily revisit cycles for any landmass at 3–10 m resolution.
Learn moreQuantized deep learning models run at the edge on NVIDIA Jetson and Raspberry Pi CM4 nodes — no round-trip to the cloud, sub-200 ms inference per image tile.
Learn moreWeb-GIS interface powered by MapLibre GL and PostGIS — supports vector tile overlays, real-time telemetry streams, NDVI heat maps, and administrative boundary queries.
Learn moreCMIP6-downscaled weather ensembles combined with ENSO teleconnections give agronomists 14-day irrigation windows and 90-day drought risk probabilities.
Learn moreComputer-vision models trained on 4M+ annotated crop-disease images detect early blight, fall armyworm, and viral infection 14 days before visible symptoms appear.
Learn moreScheduled PDF/API intelligence briefs with county-level yield estimates, drought-risk scores, and actionable recommendations — formatted for USDA FAS, RMA, and FSA workflows.
Learn moreA three-tier architecture keeps intelligence flowing — from the sensor array in the field to the analyst's dashboard in Washington — with no single point of failure.
Ruggedized IoT hubs (NVIDIA Jetson / Pi CM4) harvest multispectral cameras, soil probes, weather stations, and UAV streams. Offline-capable with local SSD buffering.
GPU-accelerated micro-DCs at USDA Service Centers aggregate, cleanse, and run AI inference on raw imagery — compressed intelligence packets sync to cloud every 15 min.
Multi-region AWS GovCloud deployment with PostGIS, Kafka streams, and REST/GraphQL APIs. FedRAMP-moderate compliant data residency in CONUS.
From the farm gate to the policy table, TerraVision Analytics delivers data-driven insights that change what's possible.
Continuous NDVI, chlorophyll index, and canopy-temperature analysis detects stress, disease, and nutrient deficiencies 10–14 days before visible symptoms emerge.
↑ 23% earlier interventionEvapotranspiration modeling and real-time soil-moisture telemetry enable variable-rate irrigation schedules, cutting water waste by up to 30% per growing season.
↓ 30% water consumptionContinental-scale early-warning systems for fungal outbreaks, insect infestations, and viral pathogens — protecting yields and reducing chemical input costs.
↓ 18% pesticide spendMachine-learning models integrate historical yields, weather ensembles, and satellite imagery for county-level production estimates 60 days before harvest.
±2.1% forecast accuracyLongitudinal datasets track shifting growing seasons, drought severity indices, and carbon sequestration to inform climate-smart agricultural policy.
30-yr trend datasetsIoT telemetry from harvesters, sprayers, and planters identifies predictive-maintenance triggers and optimizes multi-machine logistics across large operations.
↓ 14% downtime"TerraVision's edge architecture gives us the ability to monitor millions of acres in near-real time. The drought-risk scores and disease alerts have transformed how we allocate resources."
"The yield-forecasting module cut our procurement uncertainty from ±18% down to ±2.1% three months out. That margin improvement is worth tens of millions in commodity hedging."
"We integrated TerraVision's REST API in two weeks. Their PostGIS data model is clean, the GraphQL layer is responsive, and the Kafka streams feed directly into our own BI stack."
Join USDA agencies and forward-looking agribusinesses already leveraging edge-native AI to secure America's food supply and anticipate tomorrow's risks today.