Computer vision for agriculture

We detect crop problems before they cost you money.

CropVision combines AI, computer vision and drone technology to monitor your fields in real time, detect diseases early and help you increase yield.

See how it works About us

Keeping an eye on tomorrow

RECDRONE-01 · 42 M

VINEYARD · NORTH ESTATEMODEL CV-1.3

The context, according to INE

+261K

Farms in Portugal — a vast territory, impossible to watch over by hand.

Source · INE (Statistics Portugal)

+16%

Increase in fertiliser consumption in 2024 — a symptom of reactive, not preventive, farming.

Source · INE (Statistics Portugal)

Vine-leaf states our platform can already detect, from healthy to phylloxera — and the list is growing.

Platform · CropVision

Problem detected

By the time the farmer sees the pest, the damage has already begun.

Farming is becoming more unpredictable. Crop diseases, pests and inefficient monitoring lead to significant losses every season — and pests are usually detected too late, when the damage is already done.

Explore the problem

Causes

Late pest detection
Inefficient manual monitoring
Excessive pesticide use

Effects

Destroyed harvests
Economic losses
Reduced productivity
Greater environmental impact

Our solution

An automated, smarter way to watch over your crops.

We combine AI, computer vision and drone data to give the farmer a complete view of their fields — and the ability to act before, not after.

See the full solution

01 · Capture

Drones fly over and capture

Drones cover the field autonomously and capture high-resolution images of every crop row — no manual effort required.

02 · Detect

AI identifies problems early

Computer-vision models analyse every image and spot signs of pests and disease before they're visible to the human eye in day-to-day scouting.

03 · Act

The farmer decides better

Real-time alerts, pinned to the exact plot. Targeted treatment only where it's needed — lower costs, fewer pesticides.

The result: more sustainable and efficient agriculture.
Lower costs and reduced pesticide use, with continuous monitoring and data-driven decisions.

Active classifications

Pests detectable through our platform.

We started with the vineyard — one of Portugal's most valuable and most vulnerable crops. Our model tells healthy leaves apart from four major threats.

Meet every classification