Computer vision for agriculture

Keep Productivity High And Risks Low With Computer Vision For Agriculture

Advanced visual monitoring helps you detect subtle health and performance issues in crops and livestock, enabling precise actions that keep your farm running strong.

  • Multi-spectral imaging
  • On-device analytics
  • Real-time alerts
REC · ROBOT EYE LIVE30 fps · 28 ms
Leaf rust · 96%Stress zone · 92%Weed · 91%
Detections · Crops3 objects
  • Leaf rust detected96%
  • Water stress zone92%
  • Weed vs crop91%
Detection accuracy99.9%
Anomalies caught18
Model learning

Our Portfolio of Happy Customers

Prairie FeedersRiverbend FarmsOasis DairyGlobal Livestock ServicesPrairie FeedersRiverbend FarmsOasis DairyGlobal Livestock ServicesPrairie FeedersRiverbend FarmsOasis DairyGlobal Livestock ServicesPrairie FeedersRiverbend FarmsOasis DairyGlobal Livestock Services
Impact

Our Impact, By The Numbers

Powered by expert-driven agriculture computer vision, we deliver trusted solutions that keep farms efficient, productive, and ready for tomorrow.

0K+Data points processed
0K+Hours of automated analysis
0K+Acres monitored
0.0%Accuracy in detecting anomalies
0+Farm sites transformed
Capabilities

Empowering Agriculture With Next-Gen Computer Vision Technology

Drive smarter decisions across operations using advanced, scalable computer vision agriculture capabilities.

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Multi-Spectral Imaging

Reveal early stress signals in crops and animals, delivering a deeper understanding of field health and nutrient needs.

Discuss Your Project With AI Experts
Applications

Real-World Computer Vision Applications In Agriculture

Enhance productivity and make timely decisions with advanced machine vision technology for agricultural applications.

Stress zone · 93%

Precision Crop Monitoring

Utilize high-resolution imaging & drone crop monitoring to assess plant health, detect stress factors, and optimize input application.

Weed · 91%

Automated Weed Detection

Implement vision systems to identify and differentiate weeds from crops, enabling targeted herbicide application.

245.8 tons

Yield Estimation

Employ image processing in agriculture to predict crop yields accurately, aiding in harvest planning and market forecasting.

Leaf rust · 96%

Disease and Pest Identification

Detect early signs of disease and pest infestation through visual cues, facilitating timely intervention.

Moisture 8%

Soil Condition Assessment

Analyze soil texture and moisture levels via spectral imaging to inform irrigation and fertilization strategies.

Stage 2 · veg.

Crop Phenology Tracking

Monitor crop development stages to optimize management practices and improve harvest timing.

Grade A · 97%

Produce Grading and Sorting

Automatically classify produce by size, color, and quality to enhance consistency, reduce labor, and increase output.

N deficit · 90%

Nutrient Deficiency Detection

Identify visual symptoms of nutrient deficiencies to guide precise fertilization and enhance crop health.

Ready · 88%

Harvest Readiness Assessment

Determine optimal harvest times by analyzing crop maturity indicators, ensuring quality and reducing losses.

Experience the Power of Computer Vision in Agriculture

Stay proactive with precise insights that keep fields, animals, and assets performing at peak efficiency.

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Insights

AI Powered Clarity That Translates To Control

Computer vision for agriculture transforms raw visual data into actionable insights that drive profitability and efficiency.

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vision.aarvexa / alerts
Live alerts Monitoring
  • Leaf rust · Row 47Block C · 2 min ago
    Review
  • Heat stress · Pen 4Barn 2 · 6 min ago
    Review
  • Valve leak · Zone 9Irrigation · 11 min ago
    Review
  • Lameness risk · Cow #118Pen 6 · 18 min ago
    Review
How it works

Delivering Expert Designed Computer Vision Solutions

Expert-crafted computer vision for agriculture ensures precise data flow in real-time.

Cloud Inference APIEdgeDocker
01 · Input Source

Cameras, drones, phones and sensors feed raw images and video.

  1. Input Source

    Cameras, drones, phones and sensors feed raw images and video.

  2. Data

    Images are labeled, cleaned and organized into training sets.

  3. Model

    Vision models are trained and validated on your farm data.

  4. Deployment

    Models run in the cloud, at the edge or in containers.

  5. Continuous Learning

    Field feedback retrains the model so accuracy keeps improving.

Case study

Our Proven Success In Cattle Counting

See how ranchers count smarter and operate leaner with our cattle counting software.

Case study

Australian Beef Producer

Description

To eliminate manual counting errors, Australia's 2nd largest beef producer adopted AI-powered cattle counting via drone footage and implemented a real-time, computer vision monitoring system for livestock.

  • Reduced Cattle Counting Errors
  • Real-Time Livestock Tracking
  • Increased Operational Efficiency
  • Reduced Operational Costs
Find Out How We Did It
DRONE FEED · PADDOCK 7Counted 0 / 9
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Ready To See What Your Farm Is Missing?

Book a free consultation with the Aarvexa computer vision team and map out a focused pilot for your fields, herd or equipment.

Let's Connect
FAQ

Frequently Asked Questions

Straight answers on getting started, computer vision use cases, data and technology, pricing and who we are.

Start with a free consultation. We review the problem you most want to solve, the cameras, drones or devices you already have, and the images you can capture, then plan a focused pilot with a clear baseline.

Yes. A single camera or a drone flight can already deliver value, for example counting animals, spotting weeds or flagging stressed plants. Cloud processing and subscription pricing mean you do not need a large IT team.

One or two high-impact use cases first. A single workflow, such as cattle counting in one paddock or disease detection in one crop, makes it easy to prove ROI before you scale to more sites.

Most pilots move from discovery to a working proof of concept in a matter of weeks, depending on data availability and the hardware involved. We confirm the timeline in your project plan.

A short description of the problem, sample images or video if you have them, details of your cameras, drones or equipment, and the systems the results should connect to.

What can we help with?

We'll only use these details to reply to your inquiry.