REQUEST FOR PROPOSAL (RFP)
Agri AI Collect Deployment in Kharif 2026-2027
Closing Date for Submission
June 15, 2026, at 23:59 PM
LEHS is a charitable organization 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.
This RFP is intended for deployment with multiple partners on the field for data collection in Marathi language and annotation during the Kharif 2026 season.
India’s agriculture sector is driven by over 93 million smallholder farming households, with nearly 90% owning less than 2 hectares of land (NDTV Profit). While schemes like PM-KISAN offer income support (Wikipedia), smallholders still face barriers to accessing premium markets. Certifications such as India Organic and GLOBALG.A.P. are essential economic tools—organic produce can fetch 20–50% price premiums, and the organic market nearly doubled from ?169 crore in 2017–18 to ?330 crore in 2022–23 (Mint). However, manual and inconsistent data practices delay audits and exclude many farmers from timely certification. To tackle this problem among many others in the agriculture data ecosystem, India is rolling out AgriStack, a national digital agriculture infrastructure, with over 3.7 million Farmer IDs created and Digital Crop Surveys deployed in 436 districts (Indian Express, AgriStack).
The current ecosystem is fragmented, analog, and heavily reliant on manual processes. Farm-level data— critical for audits and certification—is often recorded by hand, lacks standardization, and is frequently incomplete or backfilled after the fact. Field workers, NGOs, and certification bodies struggle with disparate reporting formats, linguistic barriers, and data inconsistencies that make verification cumbersome and timeconsuming.
The implications are significant:
- Auditors spend excessive time validating claims, often through costly physical inspections and farmer interviews. (Mongabay)
- Certifying agencies face mounting pressure from international regulators due to inconsistent data quality. (Optimize IAS)
- Farmers are frequently excluded from timely certifications, missing out on seasonal market windows and associated economic benefits. (101 Reporters)
- India’s credibility in global agri-trade is at stake—as seen in recent EU actions tightening import rules on Indian organic products due to traceability concerns. (European Commission, 2021)
To address these challenges and enable scalable, verifiable digital records, Wadhwani AI is initiating a largescale deployment effort during the Kharif 2026-2027 season. This deployment will involve on-the-ground data collection and annotation by identified partner agencies in the state of Maharashtra to collect data in Marathi language. Participating agencies will be responsible for executing the deployment with farmers, and are expected to propose the number of farmers they can effectively reach and support during this season.
This RFP invites multiple highly qualified agencies, including Agricultural Universities, Krishi Vigyan Kendras (KVKs), CGIAR institutes, NGOs, Farmer Producer Organizations (FPOs), and CSR foundations to participate in the pilot deployment by conducting field-level data collection and annotation. Selected partners will be compensated for their deployment activities, and further details regarding scope, targets, deliverables, and payment terms will be outlined in the subsequent sections of this document.
Note: We’re not charging any fee from the farmers or implementing partners in this case.
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III.
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Overview of Geography
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Geographies
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Languages
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Crops
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Maharashtra
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Marathi
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Crop Agnostic
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Or any other state in India where the partner wishes to collect data in Marathi language
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Marathi
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Crop Agnostic
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The selected partner will:
- Onboard 10,000 farmers facilitating app download, registration, and usage, enabling farmer diary completion, and supporting 1,000 AgriAI certifications.
- Mobilize and onboard farmers, extension workers, and supervisors.
- Support app download, registration, and application usage.
- Train extension workers in certification-aligned form-filling. This training will emphasize the use of the application's audio-based Q&A functionality as focus for completing certification-aligned 'forms' or data fields.
- Assist farmers in capturing real-time crop cycle data with a focus through audio-based question-andanswer sessions.
- The collected data, through Q&A, must adhere to a predefined data schema to ensure consistency and facilitate downstream processing for certification and ML model training.
- The data collected, specifically through the audio Q&A format post-processing, must be in a state ready for submission to certification bodies with a possibility of minor correction at org's end' processes, ensuring it meets all relevant audit requirements.
- Monitor data quality and provide supervision.
- Collect user feedback from at least 10% of users to inform future improvements of the Agri AI Collect application and underlying ML models.
Submission Details
All responses to this RFP must be received no later than June 15, 2026. The proposal should be submitted only through e-mail in PDF format addressed to the Procurement Team in the below-given e-mail id: rfp.lehs@wadhwaniai.org. The email's subject line must contain the reference number and title of the RFP 3.0 -AgriAI Collect Deployment in Kharif 2026-2027 – WIAI (Name of the Agency).
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.