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Unlocking Efficiency: Leveraging Large Language Models for Automated Sales Order Processing

Automating data extraction for incoming sales orders presents a significant challenge, particularly when dealing with orders received via email in natural language. While various automation methods exist for structured and semi-structured order formats, such as electronic data interchange, web portal integration, and intelligent document processing, handling unstructured natural language has historically posed difficulties. However, with the emergence of large language models (LLMs), this landscape is changing.

LLMs enable us to transform unstructured content, like the following example:

“Can I order a 3m Harvest Circle Kit to the yard ASAP please. Order number AAT086.”

into structured content:

LLMs can go beyond simply structuring content and be utilised to match items from natural language to a product catalogue:

“Please can I order the following:

AP300 Water Resistant Boot size 10 in black
A pair of size 8 safety trainers, cheapest you have, black preferably
Murray black waterproof boots size 10
A set of the knee pads you have on offer at £15.99″

Yielding tabulated and accurately matched results.

The application of LLMs in real-world scenarios demonstrates their potential to deliver outstanding outcomes.


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