Technology

The Intelligence Behind the Machine

Curanova's technology stack spans satellite orbit to field edge — a multi-layer AI pipeline that processes petabytes of agricultural data to drive real-time autonomous decisions on every robot in the fleet.

AI neural network visualization

Deep Learning Vision Models

CNN and transformer architectures processing 4K field imagery at 30fps in real time

GPU data center server infrastructure

GPU Cloud Infrastructure

NVIDIA GPU clusters and AWS cloud services powering Curanova's AI pipeline at scale

AI Models

The Brain: AI Intelligence

Every Curanova robot runs a full AI inference pipeline on-device — seeing, deciding, and acting without requiring cloud connectivity.

Data Inputs

  • Satellite multispectral imagery (NDVI, NDRE, LAI vegetation indices)
  • Drone-captured RGB and thermal imagery at 4K resolution
  • In-ground soil sensors: NPK, pH, moisture, temperature
  • Hyperlocal micro-climate weather feeds at 15-minute intervals
  • Historical yield and input cost data per field zone

AI Predictions & Outputs

  • Sub-millimeter weed location and species classification
  • Localised pest pressure heatmaps with 2-week forward forecast
  • Crop disease detection 7–14 days before visual symptoms
  • Economic optimum harvest timing (brix + market price signals)
  • Variable-rate fertiliser prescription maps at sub-metre resolution

Models & Techniques

Convolutional Neural Networks (CNN)

Primary model for real-time plant, weed, and disease identification from robot cameras. Trained on 10M+ labelled agricultural images.

Vision Transformer (ViT)

Used for satellite and drone imagery where full-field context matters. Achieves 95%+ disease detection accuracy from aerial views.

Gradient Boosting & Random Forest

Tabular soil and weather data models powering yield prediction and variable-rate input prescription at sub-metre resolution.

Federated Learning

Models continuously improve from real fleet data without exposing raw farm data. Local privacy preserved, global accuracy improves.

Infrastructure

How We Use Cloud & GPU Infrastructure

Enterprise-grade cloud and edge compute that scales from a single pilot farm to a continent-wide autonomous robot fleet.

How We Use AWS

Cloud Scale & AI Services

We use AWS to host backend APIs, store user and product data securely, run AI workflows, manage authentication, deploy scalable databases, serve frontend assets, monitor performance, and support future machine learning features through Amazon Bedrock and related AWS AI services.

Amazon S3Petabyte-scale storage for satellite and drone imagery datasets
RDS (PostgreSQL)Structured farm telemetry and fleet operational data
Lambda / ECSServerless fleet orchestration and async processing pipelines
CloudFront CDNLow-latency farmer dashboard delivery globally
Amazon BedrockGenerative AI for natural-language farm insights and reports
CloudWatchReal-time infrastructure monitoring and alert pipelines

How We Use NVIDIA

GPU Compute & Edge AI

We plan to use NVIDIA technologies to accelerate AI model development, optimize inference, process visual/audio/data workloads, and improve real-time AI performance as the platform scales. Jetson modules on every robot enable on-device inference without internet dependency.

CUDA ToolkitGPU-accelerated model training on computer vision datasets
TensorRTModel optimization for maximum inference speed on edge hardware
Jetson OrinEdge AI modules on every robot — real-time inference offline
Triton InferenceCloud model serving at scale with dynamic batching
RAPIDSGPU-accelerated analytics for large agricultural sensor datasets
DeepStream SDKMulti-camera real-time video analytics on robot hardware
Architecture

System Architecture

From field edge to cloud — a complete AI pipeline with no gaps.

Field Sensors

  • Soil NPK/Moisture
  • 4K Robot Cameras
  • Weather Station
  • Drone Imagery

Robot Edge AI

NVIDIA Jetson Orin

  • TensorRT Inference
  • Real-time CV (30fps)
  • Laser Control
  • Local Decisions

AWS Cloud

  • S3 Data Lake
  • ML Model Training
  • Fleet Orchestration
  • Amazon Bedrock

Dashboard & API

  • Live Fleet Map
  • AI Alerts
  • Farm Analytics
  • Mobile App
⟵ Field Sensors   →   Edge AI (Robot)   →   AWS Cloud   →   Farmer Dashboard ⟶
Trust & Security

Your Data. Your Farm. Your Control.

Curanova is built on the principle of farmer data sovereignty. Your field data is yours — we are stewards, not owners.

🔒 Encryption at Rest & In Transit

AES-256 at rest, TLS 1.3 in transit. No raw data is ever accessible without authenticated credentials.

👤 Data Sovereignty

Clear opt-in consent before any data is used for model improvement. Farmers retain full ownership of their field records.

🛡️ GDPR & NDPR Compliance

Compliant with Nigeria's National Data Protection Regulation and EU GDPR. Regional data residency options available.

Agricultural drone collecting precision data over crops

Drone Data Collection

High-altitude imaging feeding real-time AI analysis across the entire farm

See It Live

Watch the AI in Action

Request a demo and see the Curanova AI system process real field data live. Our engineering team will walk you through every layer of the stack.

Request Demo →