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Project Proposal

AI for Smarter Irrigation ​​​​

Executive Summary

Durra.ai is an AI-powered software platform that enables Saudi farmers to conserve water and increase yields by turning existing farm data into precise irrigation recommendations. Unlike hardware-heavy solutions, Durra.ai operates as the intelligence layer, integrating satellite imagery, IoT sensor data, and weather feeds from partners.


This software-first approach ensures affordability, rapid deployment, and scalability, directly supporting Saudi Vision 2030 goals for water security, food self-sufficiency, and sustainable agriculture. 

durra ai icon

The Challenge​

Agriculture consumes over 80% of Saudi Arabia’s freshwater, with 35–40% wasted through inefficient flood irrigation. 

Water scarcity threatens both national food security and the economic sustainability of farming.

Farmers and policymakers lack a validated, cost-effective decision-support tool for irrigation optimisation. 

The Durra.ai Solution


Durra.ai acts as the AI brain for irrigation:

Inputs

Satellite imagery, IoT sensors, and weather feeds (via partners).

Core AI Models
  • Time-series forecasting for daily irrigation demand.
  • Regression models linking soil moisture, crop stage, and weather.
  • Deep learning (CNNs) for NDVI imagery to detect stress before visible damage.
Outputs

Farmer-friendly dashboards and APIs providing clear, crop-specific irrigation guidance (when, where, and how much to irrigate).

Year 1 Project Plan (12 Months)


Goal: Deliver validated pilot results within 12 months.

Months 1–3
  • Build MVP software platform.
  • Formalise partnerships (MOEWA, KAUST, Almarai).
  • Select pilot farms.
  • Baseline setup (flow meters, soil data, yield history).
Months 4–7
  • Vegetable pilot trials (short cycles → tomatoes/cucumbers).
  • Early AI calibration and interim results.
Months 6–12
  • Wheat pilot trials (longer growth cycle).
  • Ongoing AI optimisation.
Month 12
  • Independent validation (KAUST/KSU).
  • Publish Year 1 results: water savings, yield improvements, ROI.

Deliverables

  • Software MVP operational.
  • Partnership agreements signed.
  • Pilot results validated (20–40% water savings, 20–30% yield improvements).
  • ROI cases for small, medium, and enterprise farms.

€1M
Year 1 Budget

Investment and Funding Structure

€300K Co-Investment

€150K — Founder & company (Dr. Abrar Zafar)

€150K — Seed investors

30%

€700K Grant

Saudi Innovation Growth Program (SIGP)

€1M


This blended structure demonstrates founder commitment + leveraged private capital, ensuring SIGP funds catalyse maximum impact.

Validation and Scientific Rigour

  • Pilot farms will track baseline water and yields.
  • AI-guided irrigation tested vs control plots.
  • Independent validation by KAUST/KSU.
  • Evidence-backed targets (FAO, USDA, UC Davis, Kansas State):

    20–40% water savings (crop- and method-dependent).
    20–30% yield improvements.

  • Continuous learning models adapt each season to Saudi soils and climate.

Adoption & ROI

Durra.ai runs on a tiered SaaS subscription model:

Farm Size Example Pricing Water Savings Value of Savings Yield Gain ROI (after subscription)
5 ha (smallholder) ~€10/ha/year → €50/year ~20,000 m³ ~€12K +20% 3–4×
50 ha (medium) ~€8/ha/year → €400/year ~200,000 m³ ~€60K +22% 4–5×
500 ha (enterprise) custom SaaS licence ~2M m³ ~€600K +25% 5×+

Clear affordability: subscription cost is <1% of annual savings for all farm sizes.

Partnerships and Scale-Up

Government

MOEWA, Saudi Water Authority (policy, national water data). 

Corporate

Almarai, NADEC (pilot farms, adoption scaling).

Research

KAUST, King Saud University (independent validation, calibration). 

Scaling Roadmap

Year 2–3

Expand to 20+ farms in KSA; SaaS commercial launch.

Year 4–5

Extend to fodder crops and regional expansion via partners (e.g., ICARDA, FAO, GCC agri programs) in Egypt, Sudan, Morocco.

Team

Founder – Dr Abrar Zafar

20+ years in IT systems, AI workflow design, regulatory compliance.

AI Engineering Lead

ML and computer vision specialist (crop stress detection).

Agronomy Advisor

KAUST/KSU partnership for crop science expertise.

Project Manager

Coordinates pilots, partnerships, and farmer onboarding.

Business Lead

SaaS pricing, adoption strategy, government relations.

Risks and Mitigation

Risk Potential Impact Mitigation
Farmer adoption slower than expected Low subscriptions, limited ROI proof Tiered pricing + government subsidies + ROI demo farms
Data access delays (sensors/satellites) Incomplete model inputs Multiple data providers, fallback to weather APIs
Climate anomalies (heatwaves, floods) Reduced reliability of early models Continuous retraining, adaptive AI, seasonal recalibration
Partnership delays Slower scaling Secure MoUs in Year 1, diversify partners

KPIs (Year 1)

  • 3 pilot farms (5, 50, 500 ha).
  • Baselines measured and reported.
  • Independent validation (KAUST/KSU).
  • Documented 20–40% water savings.
  • Documented 20–30% yield improvements.
  • ROI demonstrated across farm sizes.
  • SaaS pricing tiers tested and validated with farmers.

Impact

Durra.ai delivers a scientifically validated, software-first solution that:

  • Saves 20–40% of irrigation water.
  • Improves yields by 20–30%.
  • Demonstrates clear ROI for all farm sizes.
  • Strengthens food security while reducing aquifer depletion.
  • Aligns directly with Saudi Vision 2030 policy priorities.
  • Positions Saudi Arabia as a regional hub for AI-driven water-smart agriculture.

The Future of Water Starts Here

Durra.ai is more than a technology platform. It is a national opportunity to save water, strengthen food security, and position Saudi Arabia as a global leader in sustainable resource management.

By bridging farmers, policy makers, and advanced AI, we are creating a future where every drop counts — from the field to the Kingdom’s national strategy.

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