How does precision weed spraying work?

Models distinguish crop from weed at driving speed, such as 15mph, and feed smart sprayers so only invasive plants are targeted, cutting herbicide cost by up to 80%.

Can AI identify specific pests and diseases?

Yes. Agronomists snap a leaf photo and the AI names the pathology, for example corn blight at a given stage, and recommends the correct fungicide application.

How does fruit counting work?

A camera rig drives down the row and the AI counts every apple, grape cluster, or almond, producing a yield density heatmap to plan picking labor.

Can we know yield before harvest?

Yes. Visual counts of fruit, pods, or ears give estimates weeks ahead, so you can lock in futures contracts early.

Does it cover soil health?

Yes. Spectral analysis helps identify water stress and nutrient deficiency, supporting soil health decisions zone by zone.

Which data sources do you use?

Satellites such as Sentinel-2, drones such as MicaSense, and ground robots, fused for farm-wide and leaf-level views.

What is hyperspectral or red-edge analysis?

Plants reflect non-visible light differently when stressed. Analyzing NIR and red-edge bands reveals water or nutrient stress days before the human eye can.

How are overlapping fruit separated?

We use instance segmentation models such as Mask R-CNN to separate individual berries or pods in a cluster for accurate counts.

Do you work with our imagery provider?

Yes. We ingest imagery from common satellite, drone, and robot sources and adapt to your formats.

Can it run at the edge?

Yes. Models can run on drones, sprayers, or gateways for real-time decisions without relying on a connection.

How do results reach our machinery?

We export prescription maps as Shapefiles compatible with platforms such as Climate FieldView or John Deere Ops Center for automated machinery control.

Can it plug into our existing farm software?

Yes. APIs and data pipelines connect to farm management and GIS tools so insights fit current workflows.

Is there a mobile app option?

Yes. Mobile apps let agronomists capture photos and receive diagnoses and recommendations in the field.

Both are available to match your infrastructure and data policies.

Do you offer a pilot first?

Yes. A scoped pilot on one field or block proves value before wider rollout.

What results can we expect?

Reference outcomes include up to 80% lower herbicide cost and avoiding much of the 60% chemical waste of blanket spraying. Actual results vary by farm.

How do you measure ROI?

We agree on metrics up front, such as chemical cost per acre, detection lead time, yield estimate accuracy, and labor hours.

How accurate are the models?

Accuracy depends on crop, imagery, and conditions. We validate on your own data and tune before rollout.

Can you run it for us?

Yes. Managed support covers monitoring, retraining, and new crops or use cases after launch.

Where do I start a conversation?

Use any Request A Demo button and we will reply with a scoped proposal.

Smart Farming & Crop Intelligence

AI Smart Farming & Crop Intelligence. See The Disease Before The Symptoms.

For commercial growers, agronomists, and drone service providers. We build tailored AI solutions that detect weeds, analyse soil health, and predict crop yields from satellite or drone imagery, automating the scout's eye.

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Aarvexa hyperspectral crop analysis

0%Herbicide cost reduced

0%Spray waste avoided

0 daysEarlier stress detection

CROP VISION · WEED DETECTIONRGB

LIVE

Reading RGB band…

SPECTRAL SIGNATURE

Healthy vs. stressed

DIAGNOSIS

Palmer amaranth0%

Crop0%

Other0%

YIELD ESTIMATE

0.0 t/ha

PRESCRIPTION MAP

Building zones…

SPRAY ENGINEanalyzing…

Herbicide−80%

Spray area−60%

Early warning+6 days

Hyperspectral AI · see it early

The problem

Why Walking In The Field Is Obsolete?

Traditional crop scouting relies on random sampling. You check 1% of the field and guess the rest. Relying on manual labor or generic NDVI maps creates three critical yield blockers:

The "Green Blur" Problem

Standard NDVI tells you a plant is stressed, but not why. Is it nitrogen deficiency? Rust? Spider mites? Our Hyperspectral AI diagnoses the specific root cause.

Weed Resistance

Spraying the whole field wastes 60% of your chemical budget and builds resistance. Our "See & Spray" logic detects weeds (e.g., Palmer Amaranth) in real-time to trigger spot-spraying nozzles.

Harvest Surprises

You find out the true yield only when the combine runs. Our yield estimation models count fruit/pods/ears visually weeks before harvest, allowing you to lock in futures contracts early.

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Solutions

Solutions For The Digital Acre

Automated Weed Detection (Precision Spraying)

Reduce herbicide costs by 80%. We train models to distinguish "Crop" vs. "Weed" at 15mph. This data feeds into smart sprayers (John Deere/Raven) to target only the invasive plants.

Pest & Disease Diagnosis

For mobile apps. Agronomists snap a photo of a leaf; the AI identifies the specific pathology (e.g., "Corn Blight - Stage 2") and recommends the correct fungicide application immediately.

Fruit Counting & Yield Forecasting

For orchards and vineyards, we drive a camera rig down the row. The AI counts every apple, grape cluster, or almond, generating a heatmap of "Yield Density" to optimize labor allocation for picking.

How we build

How We Engineer Precision?

Step 1: Multi-Source Ingestion

We fuse data from satellites (Sentinel-2), drones (MicaSense), and ground robots. This gives us "Macro" scale (the whole farm) and "Micro" scale (individual leaf health) simultaneously.

Step 2: Hyperspectral Analysis

Plants reflect light differently when stressed, even before they turn yellow. We analyze non-visible light spectrums (NIR/Red Edge) to detect water stress or nutrient deficiency days before the human eye can.

Step 3: Instance Segmentation

Counting overlapping fruit is hard. We use Mask R-CNN models to separate individual berries or pods in a cluster, ensuring accurate inventory counts.

Step 4: GIS Integration

A heatmap is useless if it's not actionable. We export "prescription maps" (Shapefiles) compatible with Climate FieldView or John Deere Ops Center for automated machinery control.

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Tech stack

Our Tech Stack

Technical Stack & Expertise

Generative AI & Models

ChatGPTClaudeLLaMAGeminiDALL·EWhisperStable DiffusionCustom fine-tuned models

Frameworks

PyTorchTensorFlowHugging FaceLangChain

Platforms & Acceleration

OpenAINVIDIA TensorRTRay

Aarvexa AI leverages the world's most powerful AI frameworks, models, and acceleration platforms to build secure, scalable, and production-ready AI solutions. Our expertise spans generative AI, deep learning, MLOps, and high-performance inference.

FAQ

Frequently Asked Questions

Straight answers on smart farming: weed detection, disease diagnosis, yield forecasting, and results.

It uses satellite, drone, and ground imagery with computer vision and hyperspectral analysis to detect weeds, diagnose crop stress, and forecast yields, automating the scout's eye.

Manual scouting samples roughly 1% of a field and guesses the rest. AI analyzes every plant, so problems are found earlier and treated precisely.

Commercial growers, agronomists, orchards and vineyards, and drone service providers.

Standard NDVI shows a plant is stressed but not why. Hyperspectral AI separates causes such as nitrogen deficiency, rust, or spider mites.

Use the Request A Demo button. We review your crops, imagery sources, and goals, then propose a focused first use case.