RFP-Data Annotation for Foundational Numeracy Tool in UP
Description
REQUEST FOR PROPOSAL (RFP)
Data Annotation for Foundational Numeracy Tool in UP
Closing Date for Submission
<August 21, 2026>
INTRODUCTION
Wadhwani AI is the flagship Artificial Intelligence (AI) initiative of Lord’s Education and Health Society, 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, LEHS - 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 LEHS - Wadhwani AI to identify a dedicated partner to execute a large-scale handwriting data annotation 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, LEHS - 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 annotation of these worksheet images to generate highquality 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 annotation program to label handwritten student responses from paper-based numeracy assessments. The annotated 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 fillin-the-blank number tasks, where students write their answers in predefined boxes. The annotated data will support the development of AI systems that automate worksheet evaluation and generate diagnostic insights to help identify foundational numeracy gaps among students.
Content Type: Handwritten responses to foundational numeracy questions
Script: Hindu Arabic numerals (0–9) and simple mathematical responses/symbols
Age group of students: 7 - 9 years old
Time for completion: 2 weeks
SCOPE OF WORK
Data Annotation: Handwritten Numeracy Assessment Worksheets:
The project involves annotation of handwritten student responses from paper-based numeracy assessments. The annotated dataset will be used to train and evaluate OCR models that recognize handwritten Hindu Arabic numerals and simple mathematical responses from structured answer boxes.
The annotation partner will be responsible for transcribing student responses from worksheet images using their own annotation tool and adhering to a custom annotation schema.
Data Annotation Volume:
The project requires annotation of approximately 9,000 worksheet page images. Each worksheet page will be treated as a single annotation unit, containing multiple questions with predefined answer boxes.
The worksheets include foundational numeracy problems such as addition, subtraction, and fillin-the-blank tasks, where students write responses in structured boxes.
Submission Details:
All proposals to this RFP must be received no later than 21st August 2026. The proposal should be submitted only through e-mail in PDF format addressed to the Procurement Team at:rfp.lehs@wadhwaniai.org. The email's subject line must contain the reference number and title of the RFP: Data Annotation for Foundational Numeracy Tool in UP.
Any proposals received after the deadline 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.
Job Email ID: rfp.lehs(at)wadhwaniai.org
Download Attachment: RFP - Data Annotation for Foundational Numeracy Tool.pdf
Documents
Description
REQUEST FOR PROPOSAL (RFP)
Data Annotation for Foundational Numeracy Tool in UP
Closing Date for Submission
<August 21, 2026>
INTRODUCTION
Wadhwani AI is the flagship Artificial Intelligence (AI) initiative of Lord’s Education and Health Society, 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, LEHS - 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 LEHS - Wadhwani AI to identify a dedicated partner to execute a large-scale handwriting data annotation 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, LEHS - 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 annotation of these worksheet images to generate highquality 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 annotation program to label handwritten student responses from paper-based numeracy assessments. The annotated 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 fillin-the-blank number tasks, where students write their answers in predefined boxes. The annotated data will support the development of AI systems that automate worksheet evaluation and generate diagnostic insights to help identify foundational numeracy gaps among students.
Content Type: Handwritten responses to foundational numeracy questions
Script: Hindu Arabic numerals (0–9) and simple mathematical responses/symbols
Age group of students: 7 - 9 years old
Time for completion: 2 weeks
SCOPE OF WORK
Data Annotation: Handwritten Numeracy Assessment Worksheets:
The project involves annotation of handwritten student responses from paper-based numeracy assessments. The annotated dataset will be used to train and evaluate OCR models that recognize handwritten Hindu Arabic numerals and simple mathematical responses from structured answer boxes.
The annotation partner will be responsible for transcribing student responses from worksheet images using their own annotation tool and adhering to a custom annotation schema.
Data Annotation Volume:
The project requires annotation of approximately 9,000 worksheet page images. Each worksheet page will be treated as a single annotation unit, containing multiple questions with predefined answer boxes.
The worksheets include foundational numeracy problems such as addition, subtraction, and fillin-the-blank tasks, where students write responses in structured boxes.
Submission Details:
All proposals to this RFP must be received no later than 21st August 2026. The proposal should be submitted only through e-mail in PDF format addressed to the Procurement Team at:rfp.lehs@wadhwaniai.org. The email's subject line must contain the reference number and title of the RFP: Data Annotation for Foundational Numeracy Tool in UP.
Any proposals received after the deadline 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.
Job Email ID: rfp.lehs(at)wadhwaniai.org
Download Attachment: RFP - Data Annotation for Foundational Numeracy Tool.pdf