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The Self-Learning AI Digital Twin for Water-Efficient Food Production

Durra is a hardware-neutral AI platform that creates a dedicated Digital Twin for every production site. By continuously learning from weather, irrigation, crop performance, energy use, and operational data, it helps growers make smarter decisions that improve agricultural water productivity while reducing resource consumption.

Unlike conventional irrigation systems that follow fixed rules, Durra becomes more accurate after every production cycle, enabling farms to continuously improve their performance over time.

Core Architecture

What Is an AI Digital Twin?

An AI Digital Twin is a dynamic digital representation of a real production site.

Durra creates a unique Digital Twin for every farm, greenhouse, or protected cultivation facility. It continuously reflects local operating conditions by integrating environmental, operational, and crop data into a living model that evolves as new information becomes available.

Site-Tailored Intelligence

Rather than applying one generic model across every farm, each Digital Twin learns from its own environment, enabling recommendations tailored to the specific conditions of that production site.

How Durra.ai Works

Durra operates as a continuous learning cycle that transforms operational data into better decisions.

01

Collect

The platform integrates data from multiple existing sources, including:

  • Weather observations and forecasts
  • Greenhouse climate systems
  • Irrigation events
  • Soil or substrate moisture
  • Crop development
  • Energy consumption
  • Operational records

02

Predict

AI models analyse this information to forecast:

  • Crop performance
  • Irrigation requirements
  • Energy demand
  • Resource utilisation

These predictions help growers anticipate changing conditions before they impact production.

03

Recommend

Based on its predictions, Durra provides practical recommendations for:

  • Irrigation scheduling
  • Climate management
  • Crop management
  • Operational optimisation

Recommendations are designed to support growers, keeping them in control of operational decisions.

04

Learn

The platform continuously compares predicted outcomes with actual results.

Every completed production cycle becomes new training data, allowing each Digital Twin to recalibrate and improve future recommendations for that specific production site.

Instead of repeating the same decisions every season, Durra continuously learns from experience.

Closed Learning Loop

Built Around Continuous Learning

Traditional agricultural software follows predefined rules.
Durra continuously improves.

Every completed production cycle strengthens the Digital Twin by incorporating real operational outcomes into future decision-making.

This creates a closed learning loop where predictions become recommendations, recommendations produce measurable outcomes, and those outcomes improve future predictions.

Over time, each farm develops its own growing intelligence, making recommendations increasingly accurate and valuable.

Design Philosophy

Engineered for Modern Agriculture

Purpose-Built for Hot Climates

Many existing greenhouse management platforms were originally developed for temperate agricultural environments.

Durra is designed specifically for commercial food production in hot-arid and hot-humid climates where water availability is often the primary production constraint.

Rather than optimising only for crop yield, Durra jointly optimises:

  • Agricultural water productivity
  • Energy efficiency
  • Crop performance
  • Resource efficiency

This integrated approach helps growers make balanced decisions that improve both productivity and sustainability.

Hardware-Neutral by Design

Durra is software, not hardware.

The platform integrates with existing greenhouse infrastructure, sensors, irrigation systems, and farm management technologies without requiring major capital investment or equipment replacement.

This hardware-neutral architecture enables organisations to build on their existing infrastructure while introducing AI-driven decision support into daily operations.

Tailored Optimization

Site-Specific Intelligence

No two farms operate under identical conditions.

Climate, soil or substrate, irrigation infrastructure, crop varieties, operational practices, and local weather all influence production outcomes.

For this reason, Durra creates a dedicated AI Digital Twin for every production site rather than relying on a single shared model.

Each Digital Twin develops its own understanding of local conditions while benefiting from anonymised cross-site learning that strengthens the overall platform without compromising site-specific optimisation.

Comparison

Why Durra Is Different

How Durra compares against conventional solutions in protected agriculture.

Conventional Solutions Durra
Fixed rules and schedules Continuously learning AI Digital Twin
Generic models Dedicated Digital Twin for every production site
Static optimisation Learns after every production cycle
Hardware-dependent implementations Hardware-neutral software platform
Optimises individual systems Jointly optimises water, energy, and crop performance
Seasonal repetition Continuous improvement through measured outcomes
Integration & Adoption

Designed for Practical Adoption

Durra has been designed to fit naturally into existing agricultural operations.

Rather than replacing growers or existing infrastructure, the platform provides intelligent decision support that enhances operational decision-making through clear, practical recommendations.

By combining advanced AI with straightforward deployment, Durra helps commercial growers adopt digital technologies with minimal disruption while continuously improving performance over time.

Explore Durra in Practice

Discover how Durra is being deployed in commercial agriculture and how independent validation is measuring its real-world performance.

Explore Deployment & Evidence