Aerial view of precision agriculture fields
Now Onboarding Cooperatives, Agribusinesses & NGO Partners

Monitor Every Farm in Your Network. Protect Every Hectare of Yield.

CropNexa is the intelligence layer for cooperatives, agribusinesses, and government agencies managing farmer networks at scale. One dashboard gives your organization satellite precision, AI foresight, and sensor-level clarity across every member farm — and puts field-level decisions in the hands of every farmer you serve.

Built by agronomists and AI engineers who understand that a farmer network isn't a dataset — it's a living system with hundreds of decisions being made every day. CropNexa aggregates that intelligence at the organizational level, so cooperative managers, agribusiness teams, and NGO field programs can protect regional yield instead of monitoring one field at a time.

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7–14
Days Early Disease Detection
15–30%
Water Reduction
8–20%
Yield Improvement
40–60%
Fewer Scouting Hours

Live From Active Deployments

Real Farmers. Real Networks. Real Accuracy.

Active Users

50–100

Farmers actively using CropNexa daily across our current cooperative and NGO pilot networks.

Model Accuracy

70–85%

Validated detection and forecasting accuracy across live field conditions, not lab benchmarks.

Delivery Model

B2B2Farmer

Organizations license the platform; farmers get the app, SMS alerts, and dashboards for free.

The Cost of Late Information — Multiplied Across Your Network.

Every day between a problem starting and a human seeing it costs money on one farm. Across a cooperative of hundreds or a regional NGO program, that gap compounds into millions in preventable loss. These are the gaps CropNexa closes at the network level.

Late Disease Detection

5–30% yield loss

Manual scouting covers a small percentage of field area, identifying outbreaks after visible symptoms spread.

Inefficient Irrigation

15–30% excess water

Fixed watering schedules ignore sub-field needs, leading to costly over-application.

Yield Unpredictability

±20% forecast variance

Inaccurate projections complicate logistics, storage planning, and financial contracting.

Labor Shortages

40% unfulfilled hours

Skilled agronomists are scarce, making comprehensive field inspection impractical at scale.

See the Full Problem Analysis →

How CropNexa Works

1

Data Capture

Sensors, drones, satellites

2

AI Processing

CNN vision & ML forecasting

3

Decision & Alerting

Prioritized field insights

4

Action & Feedback

Variable-rate treatment

Intelligence at Scale

What It Processes

Multispectral drone imagery, satellite feeds, IoT soil moisture/nutrient sensors, local weather data, and historical yield records.

What It Detects & Predicts

Disease lesions 7–14 days early, zone-specific irrigation needs, sub-field yield forecasts, and nutrient deficiency maps.

The Architecture

CNN-based computer vision for spectral anomaly detection, time-series ML for forecasting, and real-time edge inference.

CropNexa AI Dashboard Mockup

Platform Capabilities

Crop Disease Detection

Early spectral signatures identified across 20+ bands. Outbreaks flagged 7–14 days before visible symptoms.

Precision Irrigation

Zone-specific watering schedules updated continuously. Fuses soil moisture, weather forecasts, and crop stage.

Yield Forecasting

Sub-field projections updated continuously. Improves harvest logistics, storage planning, and forward contracting.

Variable-Rate Application

Nutrient deficiency maps from imagery. Integrates with variable-rate fertilization equipment to reduce overuse.

Farmer-Facing Mobile App

The delivery layer your organization puts in every farmer's hands — SMS and app alerts ranked by severity and zone, in local language, with zero desk time required.

Organization Command Dashboard

A single pane of glass across your entire member network — field maps, treatment history, outcome logs, and automated ROI tracking by region, cooperative branch, or program.

Field sensor node hardware

Deployment Process

1

Sensor Installation

Deploy our ruggedized IoT nodes across strategic field zones in a single day.

2

Data Integration

Connect existing historical yield data, weather station feeds, and machinery logs.

3

Calibration Flight

Initial multispectral drone survey to map field topography and baseline crop health.

4

Model Initialization

Our localized AI begins analyzing streams and generating baseline forecasts.

5

Continuous Operation

Receive daily insights, predictive alerts, and variable-rate prescription maps.

Traction & Roadmap

Live Network Traction

50–100 Active Farmer Users, 70–85% Accuracy

Real usage and validated detection accuracy across current cooperative and NGO deployments.

Current Status

Onboarding Organizational Partners

Cooperatives, agribusinesses, and NGOs can go live within 60 days of signing.

Cooperative Subscription

Annual SaaS subscription priced per member farm or per hectare under management, with tiered support levels.

Enterprise API

Usage-based API licensing for agribusinesses that want CropNexa's models embedded directly into their own systems.

NGO & Government Licensing

Program-based licensing for regional yield-protection and food-security initiatives, scoped to district or national coverage.

Phase Focus Area Status
1. Core Infrastructure Sensor integration & cloud pipeline Complete
2. Vision Models Disease spectral signature detection Complete
3. Pilot Deployments On-farm validation & tuning In Progress
4. Yield Forecasting Time-series predictive models Planned Q4
5. Hardware Integrations Variable-rate sprayer APIs Planned Q1
6. Edge AI Offline localized processing Future

Leadership

Dr. Sarah Okonkwo

Johnbosco Onugwu

CEO & Co-Founder

Agronomist with 12 years in commercial crop research.

Marcus Tran

Sarah Okonkwo

CTO & Co-Founder

ML engineer specializing in computer vision & edge computing.

Meet the Full Team →

Ready to protect yield across your network?

We partner with cooperatives, agribusinesses, and NGO/government programs managing farmer networks. If your organization needs to monitor member farms, deploy field intelligence at scale, or embed our models via API, let's talk.

Email:
hello@cropnexa.xyz

Built for Scale on Enterprise Infrastructure

Global availability, edge-to-cloud synchronization, and hardware-accelerated AI.

AWS Cloud Backend

We leverage AWS for secure backend API hosting and massive scale. Time-series sensor data streams into Amazon S3 and RDS, while SageMaker manages our model inference. Real-time SMS and app alerts are powered by Lambda and SNS. As operations expand across regions, CloudFront delivers high-resolution field maps globally with zero latency. Amazon Bedrock extends our AI capabilities as we expand.

NVIDIA Accelerated AI

Processing gigabytes of multispectral imagery requires serious compute. We use NVIDIA GPUs to accelerate both training and inference. CUDA and TensorRT enable real-time anomaly detection on farm imagery. Triton Inference Server handles our multi-model serving architecture, while Jetson edge modules power on-farm localized AI for environments with limited internet connectivity.