Industry: Education / EdTech

At a glance: MyntiQ Tech built a PDF-to-Markdown ingestion pipeline with PyMuPDF for an AI learning platform for CBSE Class 9 Math. It removes repeated watermarks, links figures to their captions, and records both printed and PDF page numbers. That lets retrieval-augmented generation (RAG) answers cite the textbook page a student actually sees.

Overview

This case study covers the first engineering milestone of an AI learning platform MyntiQ Tech is designing for CBSE Class 9 Math. That milestone was turning textbook PDFs into clean, structured text a retrieval system can trust. Answer quality in retrieval-augmented generation (RAG) depends heavily on the source text, so ingestion was built first.

Business Problem

• Watermarks repeated on every page of the textbook PDFs.
• Figures were separated from their captions.
• Printed page numbers did not match PDF page numbers, so answers could not cite the page a student actually sees.

How MyntiQ Tech Helped

• Watermark removal: image hashing finds images that repeat across pages and drops them.
• Figure extraction: each figure is linked to its caption.
• Dual page tracking: both the printed page number and the PDF page number (via pdftotext) are recorded.
• RAG-ready output: Markdown with YAML front matter, ready for chunking and embedding, built with PyMuPDF.
• Platform design: Nomic embeddings, Qdrant and a BGE reranker. Queries are routed between a self-hosted Llama 3.1 8B for low-stakes questions and Claude via AWS Bedrock for teaching-heavy ones.

Business Outcomes Delivered

• Clean, structured source text for the retrieval layer.
• Answers that can cite the textbook page a student actually sees.
• Hybrid model routing that keeps low-stakes queries on self-hosted infrastructure.

Frequently Asked Questions

Why does PDF ingestion matter for RAG?
A RAG system can only be as accurate as the text it retrieves. Watermarks, figures separated from their captions, and mismatched page numbers all reduce answer quality and make citations unreliable.

How do you remove watermarks from textbook PDFs?
MyntiQ Tech’s pipeline hashes the images on each page and drops images that repeat across pages, which is how watermarks show up.

How can an AI tutor cite the right textbook page?
The pipeline records both the printed page number and the PDF page number, so answers can cite the page number printed in the student’s book.

Which models does the CBSE learning platform use?
The design routes low-stakes queries to a self-hosted Llama 3.1 8B and teaching-heavy queries to Claude via AWS Bedrock. Retrieval uses Nomic embeddings, Qdrant and a BGE reranker.

Building an AI product on your own documents? Talk to MyntiQ Tech or browse more case studies.