Apollo

Crop-disease diagnosis from a photo

Traction Founders Company The round tryapollo.uz

AgritechB2B / B2CSamarkand

Apollo is a crop-health AI. A farmer or agronomist photographs a plant leaf with a phone or drone, and the model instantly flags disease or stress and suggests the next step in the local language, on the web or via Telegram. No extra sensors or hardware are needed: just the cameras farms already use.

Traction

~$4,000

Revenue since Jan

Paying customers

$20,000

Grant received

Active users

Largest customer has paid $1,500 to date
Satellite data integration via the UzCosmos API; first demo prepared (Sep 2026)

The problem

Crop disease and stress show only once yield is already being lost. Sensors that catch them earlier are too expensive for most farms, so early detection is out of reach for smallholders.

Disease and stress show only once yield is already being lost
Early-detection sensors are too expensive for most farms
Most smallholders have no tool at all, only their own eyes

The solution

No new hardware: Apollo runs on cameras farms already own, so the cost is close to zero and it works for smallholders, not just large estates with sensor rigs or satellite contracts.

Photo - Phone or drone camera, no extra hardware
Diagnosis - Disease or stress flagged instantly
Answer - The next step, in the local language
Channels - On the web or via Telegram

The company

What makes it different

No new hardware to sell

Apollo runs on the cameras a farm already has. The cost is close to zero, so it reaches smallholders too, not only large farms that can afford sensor systems or satellite contracts.

Who it's for

Primary: small and mid-sized farmers growing cotton, wheat and vegetables
Secondary: agribusinesses that monitor multi-hectare holdings

How it makes money

Scout: free or low-cost for farmers, priced per scan
Fleet: monthly subscription for agribusinesses
Grid: API for banks, insurers and food programs

Market

$220B

Annual crop losses, pests and disease

Almost every farm can take smartphone or drone photos, and computer-vision models are now accurate and cheap enough to run in real time on an ordinary device. Together they make a sensor-free approach practical for the first time.

Competitors

Precision-farming providers - Multispectral cameras, field sensors or satellite contracts: all expensive.
Manual scouting - An agronomist walking the field; most smallholders rely on their own eyes.

Founders

Umarbek Umarov

Founder at Apollo

Umarbek built Apollo alone and sells it directly: a crop-health AI that reads a photo of a leaf, flags disease or stress and gives the next step in the local language, on the web and via Telegram.

Took 1st place at ai500, one of Uzbekistan's largest AI hackathons, with more than 1,300 teams and a first prize funded by Agrobank. Apollo has also received a $20,000 grant.

Based in Samarkand, one of the country's largest agricultural regions. The engineering choice is deliberate: Apollo runs on cameras farms already own, so it reaches smallholders, not only large estates.

Background