DeHaat: AI-Driven Crop Intelligence for Crop Planning and Advisory

DeHaat: AI-Driven Crop Intelligence for Crop Planning and Advisory

India flag

India

Agriculture

Medium replicability and adaptation

Implementing Organisation

Green Agrevolution Private Limited (DeHaat)

India, Rajasthan, Multiple districts across major agricultural regions

Private Sector

Implementing Point of Contact

Nikhil Toshniwal

Chief Digital Officer

Contributor of the Impact Story

Government of Maharashtra’s AI and Agritech Innovation Center, World Bank Group, Wadhwani AI

Year of implementation

2024

Problem statement

Smallholder farmers in India increasingly face climate volatility, pest outbreaks, and rising input costs, while most advisory systems remain generic, reactive, and weakly linked to real field conditions. Traditional agricultural extension delivers one-size-fits-all advisories that are not crop-stage specific, not aligned with imminent weather risks, and difficult to operationalise. Frontline actors such as retailers, field officers, and calling teams lack real-time visibility into regional crop conditions, limiting timely and coordinated interventions. This disconnect between advisory content and ground reality undermines the effectiveness of agricultural extension, leading to inappropriate input application, delayed pest management, and missed opportunities for preventive interventions. The challenge is to institutionalise smart farming and intelligent crop planning through regionally contextualised agronomic intelligence that operates as a continuous service rather than standalone messages or seasonal campaigns.

Submission Overview

Green Agrevolution Private Limited (operating as DeHaat) is an Indian agri-tech company that has institutionalised AI-driven regional crop intelligence to transform agricultural advisory from generic, reactive messaging into a continuous, regionally contextualised service. Operating across major agricultural regions of India, DeHaat addresses the fundamental challenge faced by smallholder farmers: climate volatility, pest outbreaks, and rising input costs compounded by advisory systems that remain weakly linked to real field conditions.

AI Technology Used

Machine Learning

Natural Language Processing, Remote Sensing Analytics

Key Outcomes

Access & Reach

Inclusion & Equity

Efficiency & Productivity

User Experience & Satisfaction

Resilience & Risk Reduction

Resource Efficiency

DeHaat's AI-driven regional crop intelligence platform is transforming agricultural advisory for 10.6 million smallholder farmers across India by replacing generic extension services with continuous, regionally contextualised decision support. By integrating satellite-derived crop health signals, hyperlocal weather forecasts, soil health data, and 200,000-300,000 monthly farmer diagnostics into a guardrailed agronomic intelligence layer, the platform generates over 26 million advisory sessions monthly with crop-stage and region-specific recommendations. The system has enabled earlier detection of 1.42 million pest and disease outbreaks over 12 months, shifted advisory from reactive to proactive prevention, and reduced inappropriate input application through context-aware guidance. Delivered through multichannel touchpoints with multilingual support, DeHaat demonstrates that responsible AI, when tightly coupled with agronomic science and embedded in trusted delivery channels, can institutionalise smart farming at scale and provide a replicable blueprint for transforming agricultural extension across emerging economies.

Impact Metrics

Number of farmers registered and accessing advisory services through AgriCentral platform

Baseline Value

Limited access to regionally contextualised advisory Farmers

Post-Implementation

10.6 million+ registered (6.4 million+ geo-mapped)

Internal Monitoring

Pest and disease detections enabling regional outbreak analysis

Baseline Value

Reactive, farmer-reported incidents Detections

Post-Implementation

1.42 million detections (12 months)

Internal Monitoring

Multilingual delivery ensuring accessibility for smallholders and first-time digital users

Baseline Value

Limited language accessibility Qualitative

Post-Implementation

Full multilingual support enabled Qualitative

Internal Monitoring

Monthly advisory sessions generated across all channels

Baseline Value

Generic, seasonal advisory campaigns Sessions

Post-Implementation

26 million+ monthly sessions

Internal Monitoring

Monthly farmer-sourced crop diagnostics processed

Baseline Value

Limited diagnostic capability Diagnostics

Post-Implementation

200 ,000-300,000 diagnostics/month

Internal Monitoring

Implementation Context

Scaled

Deployed across major agricultural regions of India

10.6 million registered smallholder farmers (6.4 million actively geo-mapped), frontline extension workers and agri-retail operators, and programme and operations teams

Key Partnerships

Soil Health Card programme, Government of India

Replicability & Adaptation

Moderate
  1. Satellite remote sensing and weather APIs, cloud computing infrastructure, mobile platform, GIS tools; AI/ML engineers, agronomists, data scientists, field teams
  2. Platform development capital, operational costs for data and infrastructure, field operations and farmer engagement, ongoing maintenance
  3. Agricultural research institutions, government agencies for data access, retail networks, farmer cooperative structures

Supporting Materials

* The data presented is self-reported by the respective organisations. Readers should consult the original sources for further details.