AI-Driven Ingestion Pipeline for Bills of Quantity (BOQ)

The Challenge

Manual entry of complex, multi-page BoQ documents was time-consuming, resource heavy and required much human co-ordination. Unlocking the value of the data in these documents was therefore an expensive process.

Our Solution

An end-to-end pipeline using Optical Character Recognition (OCR) and Large Language Models (LLMs) to extract, classify, and validate measurements and rates from unstructured PDFs into a structured database.

Key Outcomes

Reduced document processing time from weeks to hours with a 98% extraction accuracy rate.

Who benefits?

• Executive Leadership
• Finance and Risk
• IT, Data & Engineering Teams
• Product and Operations Teams
• Legal, Compliance and Security

Cost savings

• Prohibitive manual processes
• Manual data cleansing and reconciliation
• Constant training and retraining of staff
• Compliance coverage checks
• Typical outcome: 40–50% reduction in data/operational costs compared to manual processing.

Time savings

• Faster circulation of trusted data
• Consistent outputs integrate more effectively
• Pre-approved access paths reduce delays
• Standard patterns accelerate delivery
• Typical outcome: 80-90% reduction in document processing time compared to manual approach