REQUEST FOR PROPOSAL (RFP)
Data Collection for Foundational Numeracy Tool in UP
Closing Date for Submission < 10th May 2026>
Introduction:
Wadhwani AI is the flagship Artificial Intelligence (AI) initiative of LEHS, a charitable organization dedicated to building equitable and sustainable systems that bring modern technology to underserved populations in India. Our core mission is to develop, deploy, and rigorously evaluate AI-powered solutions for social impact across domains, including healthcare, agriculture, governance, and education.
In alignment with our objective to support projects of national and social significance, Wadhwani AI promotes the integration of cutting-edge technologies like AI into the Indian mainstream systems. We execute this through strategic partnerships with State and National Governments, apex institutions, international agencies, and key ecosystem contributors.
This Request for Proposal (RFP) is issued by Wadhwani AI, under the umbrella of LEHS, to identify a dedicated partner to execute a large-scale handwriting data collection project required for developing and contextualizing a Foundational Numeracy Tool for the state of Uttar Pradesh.
Background:
A significant number of students in Indian public schools lack foundational numeracy skills in the early grades, affecting their ability to progress in mathematics and other subjects. While initiatives such as the National Education Policy (NEP) 2020 and the NIPUN Bharat Mission have emphasized the importance of foundational learning, classrooms still lack scalable, data-driven tools to assess numeracy skills and identify specific learning gaps at the student level. Teachers often rely on manual grading of paper-based worksheets, which is time-consuming and limits the ability to conduct frequent and diagnostic assessments.
In response, Wadhwani AI is developing an AI-based system to automate the evaluation of paper-based numeracy assessments and provide teachers with actionable insights. The tool focuses on recognizing handwritten student responses to foundational numeracy problems such as addition, subtraction, and fill-in-the-blank number tasks. By digitizing worksheet responses using machine learning models, the system aims to reduce teacher grading effort while enabling more structured and frequent assessment of numeracy skills.
The system consists of three components:
- Assessment
- Diagnostics
- Remediation
To support the development and evaluation of the OCR models that power the assessment component, Wadhwani AI is collecting a dataset of handwritten student worksheets. We require an experienced partner to support the capturing of these worksheet images to generate high-quality labeled data for training and testing the OCR models.
Project Objectives:
The primary objective of this project is to execute a structured, large-scale data collection program to capture handwritten student responses from paper-based numeracy assessments. The collected dataset will be used to train and evaluate OCR models designed to recognize handwritten Arabic numerals and simple mathematical responses from student worksheets.
These worksheets contain foundational numeracy problems such as addition, subtraction, and fill-in-the-blank number tasks, where students write their answers in predefined boxes. The captured data will support the development of AI systems that automate worksheet evaluation and generate diagnostic insights to help identify foundational numeracy gaps among students.
For detailed information, please check the complete version of the RFP attached below.