Knaapen faced a complex and time-intensive task: linking completed work to the correct price book rules. Translating the actions of technicians into these rules based on documentation required significant manual input and follow-up. This led to inefficiencies and a heightened risk of mistakes, especially given that more than 1,000 rules often needed to be reviewed to find the right one.

There was a clear need for an automated solution—one that could use AI technology to quickly and accurately select the correct price book rules and billing rates based on the initial work order, technician input, and historical data. Knaapen also wanted the system to continuously learn and improve over time, thereby optimizing performance and significantly streamlining the workflow.

Datacation developed a smart AI solution based on a Large Language Model (LLM) that automates the linking of completed tasks to the appropriate price book rules. The model analyzes historical jobs to identify similar cases, combines these insights with the current assignment's data, and evaluates existing price book rules and their interrelationships. Using this information, the AI provides a preselection of the most relevant rules, from which the employee can make the final selection.

The solution also supports task-based jobs by automatically compiling labor hours, materials, and subcontractor services into invoice or billing lines. This makes the entire process faster, more accurate, and more efficient.

Thanks to the AI solution, Knaapen employees now immediately see the most relevant price book rules directly within their processing system. This allows them to create accurate and complete final invoices more quickly. Task-based jobs are also processed more rapidly and consistently. As a result, Knaapen not only saves time in its processes but can also shorten onboarding times for new staff, contributing to improved employee satisfaction. The system is continuously enhanced by feeding new job data into the AI model, leading to ongoing optimization of the workflow.