Agro Flow AI is an integrated, AI-driven system for managing water use and irrigation. Sensors measure, the model calculates, and the field is watered in the optimal regime.
Live data from the platform — growing throughout the Beta program
The path of a single reading — from the field to your phone.
IoT sensors continuously record soil moisture, water level, temperature and agroclimatic indicators.
Even without internet access, data reaches the cloud securely and in real time over the radio network.
Cloud AI models calculate the optimal irrigation regime, and CropAI forecasts the yield.
The recommendation reaches your phone — or the gate opens remotely and water flows to the right field on its own.
Data flows bottom-up: the farmer sees their field, the district sees its territory, the republic sees the whole network.
Sensors, weather stations and Smart Channel devices — all data flows into a single cloud platform.
We remotely monitor farms and water facilities through our platform's stations — coverage is steadily expanding.
Map: Wikimedia Commons (NordNordWest / MacedonianBoy) — adapted under CC BY-SA 3.0
A mathematical water-balance model and integrated AI optimize irrigation decisions.
A single model that captures the relationship between soil moisture, water balance, evapotranspiration and yield.
A water-balance mathematical model that optimizes irrigation decisions.
IoT monitoring and the AI decision module combined into a single control system.
A dedicated model that forecasts yield based on local agrobiological factors.
The platform runs role-specific AI agents: an agronomist for farmers, an analyst for managers, a water engineer for engineers. Each one works with your field's own data.
Field map, sensor status, and AI recommendations — all on one screen. Works on web and mobile.
The platform accounts for each field's crop type, soil, and hydromodule zone — automatically calculating the irrigation rate and water fee.
Water requirements, growth stages (Kc) and yield norms for each crop.
Read more →Soil type, mechanical composition, moisture capacity and salinity level.
Read more →The hydromodule zone sets the irrigation rate based on soil and groundwater conditions.
Read more →* These figures are a forecast based on scientific modeling and experience from similar systems. Real results will be confirmed during the pilot program.
“I used to judge irrigation by eye. Now I see every field's status on my phone — I know exactly when and how much water it needs.”
* This is a pilot-project result, honestly labeled as such — not yet large-scale, independently verified statistics. Real customer case studies will be added as the pilot program grows.
“I used to irrigate by guesswork. Now the platform tells me itself — which field, when, and how much.”
“We caught tomato disease at an early stage. Last year that same disease wiped out half our harvest.”
“We monitor every field from one screen. We only go out when there's an alert — saves time and fuel.”
If the platform helped you see real results, your feedback will be useful to other farmers. Submitted reviews are published after moderation.
Satellite data and the free calculator are included in every plan.
For small farmers
Full control with IoT and AI
For large organizations
No upfront cost, monthly lease.
We're open to partnerships. →
🚀 Beta program — free early access
Platform development, technology news, and practical agro-advice for farmers.
Why foreign models fail on Uzbek fields, and why local data accumulation is a strategic question.
Read →
Calculating WUE, typical values for Uzbekistan, and levers for improving it.
Read →
Where to place the probe, why one point is not enough, and the most frequent installation errors.
Read →Be among the first users — let's start digitizing your field today.
