Many companies are faced with the task of efficiently processing a large number of customer inquiries and orders. These orders reach the company via various channels such as e-mail, fax or telephone and often have to be transferred manually to the systems. This results in a lot of time, increased personnel requirements, high process costs and an increased risk of input errors — while at the same time increasing pressure to deliver quickly and reliably.
Together with the customer, Liquam has developed an AI-based solution that automates, structures and dynamically adapts the entire order entry process.
A practical example:
Until now, a retail company with over 200 internal sales employees required enormous resources to manually process a variety of orders every day. The process was error-prone and time-consuming. The aim was to significantly reduce manual effort through AI-based automation and at the same time ensure improved customer service.
In this project, Liquam developed a tailor-made, AI-based order entry for a retail company, which is precisely tailored to the customer's processes and systems. The starting point was a comprehensive analysis of ordering channels, formats and previous processes. The aim was to create a solution that automatically records, structures and transfers orders to existing ERP systems.
The developed solution uses AI to recognize incoming orders from emails, faxes or other formats, reliably extract content such as article numbers or quantities, and automatically start the appropriate internal process. Missing or unclear information is identified and the AI automatically creates queries for the customer.
To ensure transparency and quality, a dashboard was integrated, which shows the processing status in real time and analyses the performance of the automation. The solution can be flexibly extended, for example to include multilingual processing, image recognition (e.g. of technical drawings) or integration into customer portals.
