Job ID: 288754

RFP for the Deployment of the AgriVaani Application

Lords Education and Health Society (LEHS)

Location: India

Apply by: 09 Apr 2026

Relevant Sectors

Administration, HR, Management, Accounting/Finance

Agriculture, Livelihoods, Microfinance, Rural, Urban

Monitoring, Evaluation, Policy, Research

REQUEST FOR PROPOSAL (RFP)
 
For the deployment of the AgriVaani Application
 
Closing Date for Submission
 
April 9, 2026, at 23:59 
 
I.
INTRODUCTION 
 
LEHS is a charitable organisation in India whose purpose is to offer basic health and education for the poor. LEHS in furtherance of charitable objectives through its flagship programs, Wadhwani AI, which aims to build equitable and sustainable systems by making quality primary healthcare available and accessible to the underserved population, and to bring the benefits of modern AI technology to underserved populations by building and deploying AI solutions for social impact across domains such as healthcare, agriculture, governance, and education in India. LEHS aims to promote the integration of technologies, particularly in emerging domains like artificial intelligence and innovations into the Indian mainstream primary healthcare, education, and agriculture systems through a partnership with the State and National Government, apex institutions, international agencies, and private sector partners e.g. innovators, social enterprises and other ecosystem contributors in line with its stated objectives for the betterment of society particularly focusing on projects of national and social significance.
 
Wadhwani AI, a unit of LEHS, focuses on developing, deploying, and evaluating artificial intelligence solutions to address critical social challenges in India, particularly in domains such as healthcare, agriculture, and education.
 
LEHS aims to promote the integration of technologies, particularly in emerging domains like artificial intelligence and innovations into the Indian mainstream primary healthcare, education, and agriculture systems through a partnership with the State and National Government, apex institutions, international agencies, and private sector partners e.g. innovators, social enterprises and other ecosystem contributors in line with its stated objectives for the betterment of society particularly focusing on projects of national and social significance. In line with its mission to support projects of national and social significance, LEHS also undertakes rigorous monitoring, evaluation, and learning (MEL) activities to assess the impact, usability, and scalability of different programmatic interventions.
 
II.
BACKGROUND
Indian farmers face significant challenges due to Inadequate Extension Services. The national ratio of extension workers to operational holdings in India is 1:1162, far from the recommended ratio of 1:750. In hilly areas, the recommendation is 1:400. Fragmented Agricultural Information Systems, where data silos and limited integration limit access to timely, localised, and actionable information. Existing AI/ML tools are either proprietary, not open-source, not multilingual, or lack real-time integration. These issues contribute to poor productivity, increased economic vulnerabilities, food insecurity, and unsustainable farming practices.
 
Wadhwani AI is developing an Open-sourceable Agricultural Domain-specific Language Model (DLM), which will power a multimodal, multilingual, and contextual conversational AI application called AgriVaani that delivers localised, timely, and actionable advisories to Indian smallholder farmers and Extension Workers (EWs). It will serve as the core engine for farmer assistance, piloted after experts and internal validation. In 2025, our primary focus will be on developing a text-based conversational model fine-tuned on agriculture domain curated conversational datasets. These models aim to provide accurate and relevant responses to user queries, especially in the Indian agricultural domain.
Wadhwani AI is conducting a pilot testing and deployment of the AgriVaani Chatbot in 2026, aimed to empower farmers with AI-driven, context-specific, reliable, and actionable advisories to enhance productivity, reduce agricultural losses, and enable data-informed and profitable farming decisions.
 
This RFP invites multiple highly qualified agencies, including Agriculture Universities, KVKs, CGIAR institutes, NGOs, FPOs, and CSR foundations, to undertake the RFP for the deployment of AgriVaani Chatbot Application. Through this RFP, LEHS wishes to onboard multiple organisations that can together cover the entire spectrum of crops to take up the pilot and deployment of AgriVaani Chatbot. If the selected organisations perform well in 2026, they will be selected for deployment in 2027. Selection will be based on performance and the deliverables listed in sections IV–VI.
 
The pilot testing and deployment could be undertaken by Agriculture Universities, KVKs, CGIAR institutes, NGOs, FPOs, and CSR foundations. Organisations with presence in states of Rajasthan, Maharashtra, Gujarat, Punjab, Odisha, Andhra Pradesh and Telangana will be given preference.
 
III.
PROJECT OBJECTIVES
  • On-the-Ground Deployment and Adoption: Successfully deploy and drive the adoption of the multilingual, multimodal AI-powered conversational application, AgriVaani, among smallholder farmers and field extension workers 
  • Targeted Reach and User Engagement: Work towards reaching approximately 100,000 field users (with a focus on including at least 20% women) by the end of 2026, and facilitating over 5,00,000 user queries.
  • Provision of Contextual Advisories: Deliver accurate, timely, and contextually relevant advisories on critical agricultural topics, including crop management, pest and disease identification, weather information, irrigation, and nutrition management, among others. 
  • Demonstrate Impact: Contribute to enabling better resource efficiency, the adoption of sustainable farming practices, and the potential increase in incomes and crop yields for smallholder farmers.
IV.
SCOPE OF WORK
Applying agencies must have a user base of at least 20,000 users. Multiple agencies will be hired to achieve the total target of 1 lakh user base in different geographies.
 
Deployment phase: May 2026 - December 2026 
 
Target to Achieve: 20,000 users (minimum) and 100,000 agri-queries (including photoqueries)  
  • Test additional features, including weather, image queries, mandi (market) prices and allied sectors such as animal husbandry, poultry, sericulture, apiculture, fisheries, and agroforestry.
  • The user base includes farmers and EWs. Users must possess an Android phone (version 8.0 or above) and a stable internet connection to participate in the deployment phase.
  • The total user base must include at least 20% women farmers. 
  • Conduct periodic training and capacity building for farmers and EWs for application usage and track attendance of potential users. This includes advisories in textual and voice input and output modes. 
  • Collect photos and videos of users during training, capacity building, application usage and feedback. The protocol for these processes will be shared with the organisations during the onboarding process.
  • Collect feedback from farmers and EWs to improve the model and the overall application.
  • Feedback will be collected via in-app features and a Google form, the template for which will be shared during onboarding.
  • Facilitate the process of Wadhwani AI field-level user acceptance testing, product research, and MEL study. These studies will be carried out by Wadhwani AI members, but protocols and further details on facilitation for these studies will be shared later.
  • Help scale the application among farmers and field extension workers.
  • Carry out continuous nudges or reminders to users to encourage ongoing use of the AgriVaani application. 
  • Devise monitoring and retention strategies in collaboration with Wadhwani AI to re-engage users who become inactive.
  • Selected agencies will be required to regularly capture, maintain, and report data on a defined set of monitoring indicators provided by Wadhwani AI. These indicators will cover deployment progress, user onboarding, training conducted, application usage, and user engagement. Reporting formats, definitions, frequency, and templates will be shared during onboarding. Agencies will be responsible for the timely submission, accuracy, and completeness of indicator data.
  • Implement retention strategies to encourage continuous usage among low-engagement users.
Submission Details  
  • All responses to this RFP must be received no later than April 9, 2026. The proposal should be submitted only through e-mail in PDF format, addressed to the Procurement Team at the following email address: rfp.lehs@wadhwaniai.org . The email's subject line must contain the reference number
  • and title of the RFP: Proposal for – Deployment of AgriVaani Application – Wadhwani AI (Name of the Agency).
  • Only shortlisted agencies will receive an acknowledgement and may be invited for an e-meeting to present their proposals.
  • Any proposals received by Wadhwani AI after the deadline for submission of proposals prescribed in the timeline of this document are liable to be rejected.

For detailed information, please check the complete version of the RFP attached below. 

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