AmuFlow

Satellite-guided irrigation management

Traction Founders Company The round amuflow.org

AgritechB2B / B2GKhorezm

AmuFlow is a zero-hardware irrigation platform for existing canal systems. With no extra sensors or field equipment, AI analyses open-source satellite and soil data and delivers a daily optimal irrigation plan: by SMS or notification to farmers, and on a central dashboard for water consumer associations.

Traction

Pilot farmers, Sep 2026

100+ ha

Prospective next pilot

Field datasets benchmarked

AvtoSanoat expressed investment interest; met the head of UzCosmos's investment arm
Meetings set with a President's office water specialist and the head of AgroVentures

The problem

Agriculture is ~25% of Uzbekistan's GDP but uses 90% of its water. Irrigation still follows a rigid Soviet-era calendar regardless of weather, and rival sensor systems cost $5,000+ per farm.

Agriculture is roughly 25% of GDP but uses 90% of the country's water
Water is released on a fixed weekly day, regardless of the weather
Rain after irrigation stresses roots and wastes tonnes of water
Rival sensor systems cost at least $5,000 per farm

The solution

AmuFlow is a zero-hardware AI farm manager for Uzbek farmers. Five tools in one app (finance, journal, reminders, analysis and an AI adviser) turn each farmer's own records and satellite crop data into per-field profitability and clear, Uzbek-language advice on when and how much to irrigate.

Finance - Per-field profitability
Journal - The farmer's own field records
Reminders - When and how much to irrigate
Analysis - Satellite crop data on every field
AI adviser - Clear advice in Uzbek

The company

What makes it different

Zero-hardware

Rubicon Water and CropX need at least $5,000 of sensors per farm. AmuFlow is 100% software: no physical infrastructure, and it integrates immediately with existing canals.

Who it's for

Agro-clusters optimising resources across large areas
Mid-sized farms on the canal and ditch system, hit directly by water scarcity
Water consumer associations that regulate regional water distribution

How it makes money

Core: B2B SaaS subscription, an annual fee per irrigated hectare
Additional: B2G licence for government bodies
Future: trading water credits based on the volume of water saved, and state-subsidy integration

Market

$6.5-12.9M

SAM, Uzbekistan (4.3M hectares)

$393-786K

SOM in 3 years (~262,000 hectares)

Water resources have fallen 20% in 3 years and the shortfall is forecast to exceed 15 billion m³ by 2030. NASA POWER and SMAP open data are now accurate enough to make field hardware unnecessary. TAM, Central Asia: $13.8-27.5M.

Competitors

Global technology players - Rubicon Water (canal gates), CropX and CropIn (soil sensors, IoT): all need expensive hardware.
Traditional system - Rigid state calendar schedules and water distributors who depend on the human factor.

Founders

Alisher Ortikov

Founder at AmuFlow

Alisher works where quantum computing meets full-stack engineering. Studies at KAIST and EPFL, holds IBM's official Qiskit Advocate status and has more than five years of experience building full-stack systems.

Software engineer at Teambl, designing scalable, high-load systems and shipping them to production; previously technical lead at three startups. Author of open-source tools, including the telegraf-pagination library on npm.

The problem is personal: Alisher is a native of the Khorezm oasis in the drying Aral Sea region, where saving water and optimising irrigation is the most pressing issue.

Alisher Ilhamov

CEO at AmuFlow

Background

KAIST, South Korea: a global top-100 research and engineering university
EPFL, Switzerland: a global top-25 university
IBM Qiskit Advocate; 'Quantum Excellence' level at the IBM Qiskit summer school (2025)
Top-5 at the international Quandela Hackathon Challenge in quantum computing
Software engineer at Teambl; previously technical lead at three startups
Author of telegraf-pagination, an open-source npm library with 15 releases

Milestones

3 Sep
Agronomic model debugged against 25+ scientific validation requirements; 8 data categories reviewed

4 Sep
Model accuracy improved; interviews with 2 farmers; a possible new pilot of 100+ hectares
6-7 Sep
Pilot farmers reached 7 in total; met the head of UzCosmos's investment arm
10 Sep
Model compared against 4 sets of real field data; interviews with 3 farmers; AvtoSanoat expressed investment interest
21 Sep
Introduced to a water-resources specialist in the President's office and the head of AgroVentures; meeting set