MicrosoftScaled productionEvidence: Medium50/100

KALRO boosts Kenyan crop yields with AI-powered precision agriculture

Use case typeAgriculture optimizationUpdated Jun 13, 2026

Kenya Agriculture and Livestock Research Organisation (KALRO) implemented an AI-driven system to enhance agricultural productivity among smallholder farmers. Working with CABI, they deployed the PRISE early warning system using Microsoft Azure, Generative AI, and Earth Observation data. The solution provides zone-specific pest and weather advisories to over four million farmers via SMS and digital bulletins. Additionally, solar-powered, computer-vision pest detectors were rolled out, delivering on-site alerts in seconds for rapid intervention. This digital advisory network has been key to scaling agricultural insights and decision-making nationwide. Results included up to 30% reduction in crop pest losses and up to 40% yield increases for vulnerable farmers, illustrating how digital transformation is reshaping smallholder agriculture in Kenya. The scalable setup allows continuous improvement as new data and AI models are integrated.

Organization: Kenya Agriculture and Livestock Research Organisation (KALRO)
Industry: Agriculture
Location: Kenya
Published: September 2025

Reported outcomes

−30%

quantified impactRisk, reliability & safety

40%time

Strategic outcomes

Scale & capacityReached over four million farmersNew product / capabilityDeployed AI-powered pest early warning systemBetter decisions & insightDelivered zone-specific advisory insightsSpeed & agilityDelivered on-site alerts in seconds

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Quantified impact: 30% decrease

Nucamp BlogSep 10, 2025Blog postInferred claimMedium evidence strength

Reduction of pest losses by up to 30% in pilot regions.

Normalized claim

Time: 40%

Nucamp BlogSep 10, 2025Blog postInferred claimMedium evidence strength

Yield increases of up to 40% for vulnerable farmers through timely interventions.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Kenya Agriculture and Livestock Research Organisation (KALRO)
Provider: Microsoft
Maturity: Scaled Production
Linked source: Nucamp Blog

Digital advisories scaled to reach more than four million Kenyan farmers, supporting improved nationwide agricultural productivity

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 3

1AI-driven precision pest monitoring and early warning for smallholder farmers
2Automated advisory delivery for yield optimization using cloud analytics
3Solar-powered edge-computer vision for real-time pest detection

Frequent and severe crop pest outbreaks threaten food security and livelihood for millions of Kenyan smallholder farmers.
Limited timely access to localized pest and weather advisories for rural farmers.
Traditional detection and intervention methods are slow, resulting in delayed responses and lost yields.
Smallholders have limited technology access for real-time decision support.

Deployment of the PRISE early warning system integrating Microsoft Azure and Generative AI for data analysis and rapid advisory delivery.
Integration of Earth Observation data, weather forecasts, pest lifecycles, and agronomy datasets to produce actionable, localized insights.
Distribution of advisory content to 4 million+ farmers via SMS and PDF bulletins for accessibility.
Deployment of solar-powered, computer-vision pest detectors to deliver actionable alerts within seconds at the farm level.

Technologies

Azure Generative AI Earth Observation

Reduction of pest losses by up to 30% in pilot regions.
Yield increases of up to 40% for vulnerable farmers through timely interventions.
Digital advisories scaled to reach more than four million Kenyan farmers, supporting improved nationwide agricultural productivity.
Practical demonstration of scalable, replicable digital agriculture transformation for emerging markets.

Architecture

PRISE combines Microsoft Azure cloud and AI services, local data integration (weather, pest lifecycle, Earth Observation), Generative AI for analytics, and edge-deployed solar-powered pest detection devices, all funneling alerts and advisories via automated SMS/PDF platforms to farmers. Digital two-way channels widen access and allow for ongoing update and feedback loops between centralized analysis and frontline growers.

Sources & evidence1

Evidence: Medium50/100Evidence strength