RFP- Multilingual Image Data Collection Services for AgriAI Collect

Lords Education and Health Society (LEHS)

Apply by: 07 Aug 2026

Social, Gender, Education, Youth, Child

REQUEST FOR PROPOSAL (RFP)

For Multilingual Image Data Collection Services for AgriAI Collect Closing Date for Submission

August 07, 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. As part of its ongoing initiatives in the agriculture sector, Wadhwani AI is developing an image-to-text extraction model aimed at identifying and extracting key textual information from agricultural input product images—such as fertilizer bags, pesticide containers, and seed packets. These AI models are being trained to accurately recognize and extract product names, compositions, usage instructions, and other relevant information in English, enabling better access to product-related information for farmers and agri-extension workers. In alignment with its quality assurance framework, Wadhwani AI will conduct rigorous evaluations to assess the accuracy, consistency, and applicability of the extracted textual data to ensure the model’s effectiveness and reliability in real-world agricultural use cases.

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,