Automating Catalogue Extraction and School List Matching
Our client is a major educational publishing house that aggregates and distributes textbooks from various publishers and must understand which schools are assigning which books.
Business Challenge
Teams manually typed data from mixed-format publisher catalogues and cross-referenced hundreds of school book lists received as scans, PDFs or inconsistent digital files. This created seasonal workload, avoidable errors and delays in forecasting and print-run decisions.
Solution Strategy
We used a dual-extraction and automated comparison pipeline: AI-OCR for catalogue and school-list extraction, human verification for low-confidence fields, automated cross-referencing and natural-language analytics.
Key Capabilities
AI-OCR structured extraction
Human-in-the-loop verification
Automated cross-referencing and matching
Natural-language analytics over matched data
Technology & Architecture
- MultiLLM AI Platform
- AI-OCR
- Structured database
- Matching logic
- Natural-language analytics
Outcome
- Hundreds of staff hours saved
- 0 manual spreadsheet matching needed
- Real-time market insights through natural-language querying
- Higher consistency in catalogue and school-list processing
Client Perspective
Every summer, our team used to drown in paper, manually typing catalogues and cross-checking hundreds of school book lists just to figure out our market position. MultiLLM AI Platform’s AI-OCR automated extraction and matching, and the ability to simply ask for a chart of our market share has revolutionized our decision-making.
What This Demonstrates
This project demonstrates our ability to combine workflow analysis, software engineering, data processing and AI into an operational solution rather than treating AI as a standalone feature.
Build a Similar Solution
If your organisation has a comparable document, data or workflow challenge, we can assess the process and propose a phased solution.