Turn Parcel-Level Field Data into Better Farm Decisions

AgriTwin connects high-precision field sensing, localized AI insights, and actionable decision support in one integrated system. By collecting reliable parcel-level data and turning it into timely recommendations, the platform helps farmers act earlier, reduce risk, and make better field decisions.

AgriTwin workflow: field data collection, AI insights platform, and actionable farm decisions
From parcel-level field data to actionable farm decisions.

Farmers Already Have Data — But Not Timely Decisions

Large farms already work with weather stations, machinery data, apps, and dashboards, but this information often stays fragmented across multiple tools. At the same time, parcel-to-parcel conditions can differ significantly, with temperature and even rainfall varying across the same farm. As a result, decisions are often delayed, too broad, or simply wrong. AgriTwin is designed to reduce this fragmentation and help transform local field data into timely, actionable decisions.

The problem: fragmented farm data, parcel variability, and delayed decisions
Farmers already have data — but not timely, parcel-level decisions.

The AgriTwin Field Data Collector

AgriTwin’s field data collector is designed to capture reliable local environmental data directly from the field. Built for parcel-level deployment, it combines high-precision sensing, solar-powered operation, and NB-IoT connectivity powered by Orange in one rugged, EdgeAI-ready system.

The collector is designed not only to monitor temperature, humidity, pressure, wind, and rainfall, but also to support smarter operation in remote conditions. With adaptive communication strategies for winter resilience and flexible power configuration, it provides the sensing foundation needed for better local insights and more timely farm decisions.

AgriTwin high-precision EdgeAI field collector with solar power and NB-IoT connectivity in a wheat field
Solar-powered, high-precision field sensing built for parcel-level agricultural monitoring.

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