Topline Glass launches in-house AI order processing system

Topline Glass has developed a new AI-powered order processing system designed to improve accuracy, efficiency and customer service across its operations.

Named COLBi – short for Customer Order Logic & Build interface – the software has been developed entirely in-house by Office Manager Sam Turnock and is already being used to process a significant proportion of customer orders.

COLBi is designed to upload, read and interpret customer orders submitted in a wide range of formats, including emails, PDFs and scanned documents. Unlike traditional optical character recognition systems, the software uses artificial intelligence to understand intent, learning customer preferences and recognising variations in terminology over time.

“This isn’t just about reading text,” explained Sam. “It’s reading orders like a human would and trying to understand what the customer actually wants.”

The system is trained customer by customer, learning default specifications and preferences and retaining that knowledge permanently. This helps ensure a consistent experience for customers, while supporting the office team with shared knowledge across the business.

After two months of live use, COLBi is already processing orders for the company’s four largest customers, accounting for around 40 percent of weekly line items. The business is targeting 80 percent of orders to be processed through the system by the end of the year, with more complex orders continuing to receive manual oversight.

“For customers, the biggest benefit is accuracy,” said Sam. “Computers don’t mis-key numbers. But just as importantly, it frees our office team up to spend more time on service, advice and relationships.”

Future development plans include automated email integration, overnight order processing, and potential links to quoting and production planning systems.

Sam added: “This isn’t about replacing people. It’s about giving customers the best service we can by letting technology handle the repetitive tasks and leaving the rest to experienced staff.”

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